Unlock deeper insights into microbial ecosystems with N2 Jenomics Lab Pvt. Ltd. ' shotgun metagenomic sequencing — a powerful tool for strain-level microbiome analysis. Whether you're working in microbial ecology, agricultural biotechnology, or host-microbe interactions, our end-to-end service offers high-resolution taxonomy and functional profiling.
Shotgun metagenomic sequencing is a high-throughput, untargeted approach for analyzing the complete genetic content of all microorganisms in a given sample. Unlike amplicon-based methods that rely on specific primers, shotgun sequencing randomly fragments and sequences all extracted DNA — capturing bacterial, viral, fungal, and archaeal genomes in one go.
This method provides a more complete picture of microbiome composition, gene function, and metabolic pathways. It’s especially suited for complex environments like soil, aquatic systems, the human gut, and skin. Researchers also use it to discover novel microbes and rare functional genes not detectable by targeted approaches.

Shotgun sequencing delivers a comprehensive view of the microbiome — ideal for applications that demand depth, resolution, and functional clarity.

Key Advantages:
Shotgun vs. Amplicon Sequencing: A Quick Comparison
| Feature | Shotgun Metagenomics | Amplicon Sequencing (e.g., 16S) |
|---|---|---|
| Primer design required | ❌ No | Yes |
| Microbial coverage | All microbes (bacteria, viruses, fungi) | Mostly bacteria and archaea |
| Taxonomic resolution | High (species/strain level) | Limited (genus/species level) |
| Functional gene analysis | Yes | ❌ No |
| Novel species detection | Yes | ❌ Limited |
| Cost & data volume | Higher cost, large datasets | Lower cost, smaller datasets |
| Bioinformatics complexity | High | Low |
N2 Jenomics Lab Pvt. Ltd. offers a range of metagenomic sequencing services tailored to fit diverse research goals and sample types. Depending on your study’s complexity, microbial composition, and desired depth of functional analysis, you can select the most suitable metagenomic sequencing strategy.

Standard Shotgun Metagenomic Sequencing
Broad genome coverage | Taxonomy & function | For varied samples
Learn More ↓

Long-Read Metagenomic Sequencing
Better continuity | Complex regions | Diverse genomes
Explore Long-Read Services →

Viral Metagenomic Sequencing
Sensitive virus detection | Rare viruses | Novel discoveries
Discover Viral Metagenomics Solutions →
Project Initiation
Research goal consultation
Custom protocol design
Sequencing plan confirmation
Sample Submission & Quality Control
Sample registration and documentation
DNA quality checks (concentration, purity)
Optional DNA extraction
Library Construction
DNA fragmentation and library prep
Quality validation and method selection
High-Throughput Sequencing
Platforms: Illumina NovaSeq, HiSeq, or DNBSEQ
Read lengths: 2×150 bp or 2×300 bp
Depth customisable based on project goals
Results Delivery
Raw sequencing data
Full analysis reports, figures, and summaries
Our in-house bioinformatics team delivers journal-ready reports with clean, high-impact visualisations. From standard QC to advanced ecological statistics, we’ve got you covered.
Core Analysis
Advanced Analysis (Optional Add-ons)
All results are publication-grade, ready for manuscript inclusion or project reporting.

Unlock comprehensive insights into complex microbial communities with shotgun metagenomic sequencing. At N2 Jenomics Lab Pvt. Ltd. , our platform empowers researchers to explore microbial diversity, identify novel species, and analyze dynamic shifts across diverse environment.

| Parameter | Requirement |
|---|---|
| Sample Types | Stool, environmental samples (e.g., soil, water), purified DNA |
| Total DNA | ≥500 ng (minimum 20 ng accepted) |
| DNA Concentration | ≥5 ng/µL |
| DNA Purity (OD260/280) | 1.8–2.0 |
💡Tips:
Whether you're mapping microbial ecosystems or discovering next-generation probiotics, N2 Jenomics Lab Pvt. Ltd. delivers the data clarity and technical precision you need.

Reference
Partial results are shown below:
![]() Per base sequence conten. | ![]() Per sequence GC content. | ![]() Merged_abundance. |
![]() Merged_abundance. | ![]() KEGG_classification. | ![]() CAZy function classification. |
![]() Boxplot analysis based on bray Curtis (A), binary jaccard (B), unweighted unifrac (C), and weighted unifrac (D | ![]() PCoA analysis based on bray Curtis (A), binary jaccard (B), unweighted unifrac (C), and weighted unifrac (D). |
![]() UPGMA clustering tree.
|
1. How can host DNA contamination be minimized in metagenomic projects?
Avoiding host DNA contamination starts at the sampling stage. We recommend collecting material away from host tissues to reduce the inclusion of host cells. Additionally, using host DNA depletion kits during sample preparation can significantly lower contamination.
If a reference genome for the host is available, host-derived sequences can be computationally removed via alignment-based filtering. However, when contamination is severe and no host genome is available, data quality and interpretation may be compromised. In such cases, we recommend resolving contamination issues before sequencing.
2. What are the advantages of metagenomic sequencing over single genome sequencing?
Shotgun metagenomic sequencing captures the structure and functional potential of entire microbial communities, revealing interactions among diverse organisms.
Unlike single-genome sequencing—which targets isolated strains—metagenomics eliminates the need for culturing, making it ideal for exploring complex or unculturable microbial ecosystems. This leads to a more holistic and accurate understanding of microbial ecology.
3. How does 16S rDNA sequencing compare with shotgun metagenomics?
16S rDNA sequencing targets a conserved gene region in bacteria to assess taxonomic composition and diversity. In contrast, shotgun metagenomic sequencing analyzes the entire genomic content of all microorganisms (bacteria, archaea, fungi, viruses), offering both taxonomic and functional insights. While 16S is cost-effective and simpler, shotgun sequencing delivers higher resolution and more comprehensive data—at a higher cost and complexity.
4. How do I choose the appropriate sequencing depth and read length?
Your selection depends on the complexity of the sample and the goals of your study. High-complexity samples (e.g., soil or gut microbiota) require deeper sequencing to capture the full diversity. Common read lengths include 2×150 bp or 2×300 bp. We’ll work closely with you to recommend optimal parameters based on your project’s biological and analytical requirements.
5. How is sequencing data quality ensured?
We utilize advanced high-throughput sequencing platforms such as Illumina NovaSeq and HiSeq, combined with rigorous quality control measures at every stage—from DNA extraction and library preparation to data processing. All datasets undergo multi-step quality filtering to ensure integrity, reliability, and publication readiness.
6. Do you offer custom bioinformatics analysis services?
Yes. We provide fully customizable analysis workflows tailored to your research goals—whether it's functional gene mining, antimicrobial resistance profiling, or advanced statistical modeling. Our experienced bioinformatics team will consult with you throughout the process to ensure the results align with your scientific objectives.
Customer Publication Highlight
Abundance and phylogenetic distribution of eight key enzymes of the phosphorus biogeochemical cycle in grassland soils
Journal: Environmental Microbiology Reports
Published: 10 May 2023
DOI: https://doi.org/10.1111/1758-2229.13159
Background
Grassland soils are critical for global phosphorus (P) cycling, with microbial enzymes (e.g., phosphatases, phytases) driving organic P mineralization. This study analyzed 74 global grassland soil metagenomes to map the abundance, diversity, and environmental drivers of eight key P-cycle enzymes, including alkaline phosphatases (phoD, phoX, phoA), acid phosphatases (Nsap-A/B/C), and phytases (BPP, CPhy).
Project Objectives
N2 Jenomics Lab Pvt. Ltd. ’ Services
As a key collaborator, N2 Jenomics Lab Pvt. Ltd. provided:
Key Findings
Figures Referenced

FIGURE 1. Phylogenetic placements of the predicted proteins of each metagenome with respect to the reference bases of each enzyme.

FIGURE 2. CAP analysis linking phoD abundance to soil pH/SOC

Figure 4. Edge-PCA plots showing phoD variants in Ferralsols vs. Luvisols
Implications for N2 Jenomics Lab Pvt. Ltd. Clients
Reference