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16S/18S/ITS Amplicon Metagenomic Sequencing


16S/18S/ITS amplicon metagenomic sequencing is frequently used to identify and differentiate microbial species. Short (<500 bp) hypervariable regions of conserved genes or intergenic regions, such as 16S of bacteria and archaea or 18S/ITS of fungi, are amplified by PCR and analyzed using next generation sequencing (NGS) technology. The resulting sequences are compared against microbial databases. Applications range from identifying a single species in pure culture and characterizing the microbiota of animals or plants, to comparing species diversity and population structure from various environmental sources or geographic regions. Our specialists can advise you on the appropriate analysis for your project.
Service Specifications Demo Reports


  • Species identification
  • Gut microbial environment research
  • Microbiota diversity
  • Difference of species composition


  • Highly experienced: We have sequenced over hundreds of thousands of samples, resulting in nearly 30 published articles.
  • Outstanding service: We provide high-quality sequencing (with Q30 score ≥75%), an efficient standard workflow, fast turnaround time, and bioinformatics analyses at a cost-effective price.
  • Effective methodology: Our method features high amplification efficiency of sample DNA (>95%).
  • Comprehensive analysis: We provide expert bioinformatics analyses using the latest sequence databases and software, generating high-quality, publication-ready data.

Sample Requirements

Sample Type Amount Volume Purity
Genomic DNA

Sequencing Parameter and Analysis Contents

Platform Type Illumina NovaSeq 6000
Read Length Paired-end 250 bp
Recommended Sequencing Depth 30K/50K/100K raw reads
Standard Data Analysis
Data quality control
OTUs cluster and phylogenetic relationship construction
Species annotation
Alpha diversity analysis
Beta diversity analysis
NMDS analysis
LefSE analysis
Metastats analysis
Species T-test analysis
MRPP, Anosim, Adonis, Amova analysis
Comparative analysis of alpha diversity indices
Comparative analysis of beta diversity indices

Note: For detailed information, please refer to the Service Specifications & Demo Reports and contact us for customized requests.

Project Workflow

Sample Quality Control

Library Quality Control

Data Quality Control

Sample Preparation

PCR Amplification

Mix and Purify PCR Products

Library Preparation


Bioinformatic Analysis

Gut-dependent microbial translocation induces inflammation and cardiovascular events after ST-elevation myocardial infarction


Post-infarction cardiovascular remodeling and heart failure are the leading cause of myocardial infarction (MI)-driven death for the past decades. Experimental observations have involved intestinal microbiota in the susceptibility to MI in mice; however, in humans, identifying whether translocation of gut bacteria to systemic circulation contributes to cardiovascular events post-MI remains a major challenge.


DNA from 49 healthy people, DNA from 50 people who has stable coronary artery disease (CHD) and 100 people who has ST segment elevation myocardial infarction (STEMI).

Sequencing Strategy:

Illumina platform, paired-end 250 bp

  • Intestinal-associated bacteria is enriched in systemic circulation. Because of the highest translocation products of intestinal bacteria in STEMI patients.
  • Intestinal bacterial translocation products are associated with inflammation and left ventricular function.
  • Intestinal flora translocation promotes cardiovascular events after STEMI.

Plant growth and oil contamination alter the diversity and composition of bacterial communities in agricultural soils across China


The dynamics of microbial diversity in response to biotic and abiotic disturbances provide a sensitive indicator for evaluating the potential stability and degradation of soils in agro‐ecosystems. To determine the effect on soil bacterial communities of disturbances by plant growth (Robinia pseudoacacia) and oil contamination, we sequenced 16S rRNA genes using MiSeq technology. Abiotic and biotic disturbances, including treating the soils with sterile water, crude oil, and/or an invasive plant, altered the bacterial community structure in the soils, increased bacterial richness, and reduced bacterial dispersion.


DNA extracted from twenty‐one soil samples collected from corn fields in 19 provinces of China.

Sequencing Strategy

Illumina platform, paired-end 250bp


The microbial taxa exhibited differential responses to the plant growth and oil contamination, and the assembly of the core microbiome was changed. Moreover, the bacterial communities in the soils from warmer regions were more sensitive to the environmental changes.

The chemodiversity of paddy soil dissolved organic matter correlates with microbial community at continental scales


Paddy soil dissolved organic matter (DOM) represents a major hotspot for soil biogeochemistry, yet we know little about its chemodiversity let alone the microbial community that shapes it. Here, we leveraged ultrahigh-resolution mass spectrometry, amplicon, and metagenomic sequencing to characterize the molecular distribution of DOM and the taxonomic and functional microbial diversity in paddy soils across China. We hypothesized that variances in microbial community significantly associate with changes in soil DOM molecular composition.


DNA extracted from soil samples that were collected from 88 flooded paddy sites across four typical Chinese rice-growing regions in 2014 and 2015.

Sequencing Strategy:

Illumina platform, paired-end 250 bp


Our study demonstrates the continental-scale distribution of DOM is significantly correlated with the taxonomic profile and metabolic potential of the rice paddy microbiome. Abiotic factors that have a distinct effect on community structure can also influence the chemodiversity of DOM and vice versa.

Results of OTU cluster and annotation analysis

Species abundance heatmap

Venn diagrams

Taxonomy tree for single sample

Rarefaction curves & rank abundance curves by individual samples

Beta-diversity heatmap

Principal Component Analysis (PCA) based in OTUs

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