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Metagenomic Sequencing

Service Overview
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Metagenomic SequencingIn metagenomics, genomes from environmental samples are analyzed without the prior isolation and cultivation of individual species, and, therefore, it is a powerful technique for studying microbial communities in their natural habitat, with a broad range of applications. At Novogene, our customers can rely on our expertise in NGS to help them explore the rich genetic repertoire of microbial communities, while also benefiting from our bioinformatics expertise to help identify the species, genes, and pathways represented in their samples. Novogene provides metagenomic sequencing service with Illumina HiSeq platform and assembly-first strategy, and our bioinformatics analyses provide gene predictions, function annotations, and taxonomic annotations. Our standard analysis package includes mPATH, heatmaps, PCA, cluster analysis and other programs, generating high-quality, publication-ready data.

The Novogene Advantage

  • Highly experienced: We have completed over 400 metagenomic sequencing projects for our customers, and have published multiple metagenomic studies.
  • Outstanding service: We provide high-quality sequencing, an efficient standard workflow, and bioinformatics analyses at a cost-effective price.
  • Effective methodology: Our techniques enhance the generation of data from low-abundance species.
  • Comprehensive analysis: Expert bioinformatics analysis with three databases (KEGG, eggNOG, CAZy) provides comprehensive data on annotated genes and metabolic pathways.

Project Workflow

metagenomic sequencing project workflow

Sequencing Strategy

  • 300 bp insert DNA library
  • HiSeq platform, paired-end 150 bp

Data Quality Guarantee

  • Each sample generates at least 5-10 Gb raw data, with Q30 ≥ 80%.

Sample Requirements

  • DNA amount: ≥ 0.8 μg (for one library preparation)
  • DNA concentration: ≥ 20 ng/μl
  • Purity: OD260/280 = 1.8 - 2.0 without degradation or RNA contamination

Turnaround Time

  • Within 15 working days from verification of sample quality (without data analysis)
  • Additional 10 working days for data analysis

Recommended Sequencing Depth

  • Two strategies: 6 Gb raw data or 12 Gb raw data

Analysis Pipeline

metagenomic sequencing analysis pipeline

List of Analyses

  • Our standard analysis package includes gene prediction, function annotation, and taxonomic annotation, mPATH, heatmaps, PCA, Krona, cluster analysis, MetaStats, and OG-Taxa.
  • Our advanced analysis package includes MRPP, ANOSIM, NMDS (Non-metric Multidimensional Scaling), CCA/RAD, and LEfSe (LDA Effect Size).
Table. The following table shows sample data from metagenomic sequencing projects conducted by Novogene. The effective rate, comparing clean data to raw data, was very high, with an average of over 94%, indicating that the base calling was highly accurate.
SampleInsert Size (bp)Raw DataClean DataClean_Q20Clean_Q30Clean_ GC (%)Effective Rate (%)

Project Example

The following study utilized Novogene's expert metagenomic sequencing services.

Impacts of the Three Gorges Dam on microbial structure and potential function
Scientific Reports, 5:8605 (2015).

The Three Gorges Dam has significantly altered ecological and environmental conditions within the reservoir region, but how these changes affect bacterioplankton structure and function is unknown. Here, three widely accepted metagenomic tools were employed to study the impact of damming on the bacterioplankton community in the Xiangxi River. Our results indicated that bacterioplankton communities were both taxonomically and functionally different between backwater and riverine sites, which represent communities with and without direct dam effects, respectively. There were many more nitrogen cycling Betaproteobacteria (e.g., Limnohabitans), and a higher abundance of functional genes and KEGG orthology (KO) groups involved in nitrogen cycling in the riverine sites, suggesting a higher level of bacterial activity involved in generating more nitrogenous nutrients for the growth of phytoplankton. Additionally, the KO categories involved in carbon and sulfur metabolism, as well as most of the detected functional genes, also showed clear backwater and riverine patterns. As expected, these diversity patterns all significantly correlated with environmental characteristics, confirming that the bacterioplankton communities in the Xiangxi River were markedly affected by environmental changes caused by the Three Gorges Dam. This study provides the first comparative metagenomic insight into evaluating the impact of the large dam on microbial function.


Figure 1. Canonical correspondence analysis (CCA) shows the relationships between environmental variables and the bacterial OTUs (A) and functional genes (B). Only variables that were significantly correlated with the community (forward selection with Monte Carlo test, P = 0.05) are shown. Abbreviations: TP, total phosphorus; N-NH4, ammonium nitrogen; N-NO3, nitrate nitrogen; COD, chemical oxygen demand.


Figure 2. Variance partitioning canonical correspondence analysis (CCA) shows the relative effects of multiple variables on the composition of bacterial taxa (A) and functional genes (B). The squares represent the effect of individual variables by partitioning out the effects of the other variables. The ellipses between the squares represent the combined effects from the variables on either side of the ellipse. The combined effects of all variables are shown by the ellipse in the center. The square at the bottom of each figure represents the effect that could not be explained by any of the variables tested. Abbreviations: TP, total phosphorus; N-NH4, ammonium nitrogen; N-NO3, nitrate nitrogen; COD, chemical oxygen demand.

Examples of Publications Using Novogene’s Services

Environmental Science & Technology, 49:1095 (2015)Prevalence of antibiotic resistance genes and bacterial pathogens in long-term manured greenhouse soils as revealed by metagenomic survey.
Water research, 76:43 (2015)Metagenomic insights into Cr (VI) effect on microbial communities and functional genes of an expanded granular sludge bed reactor treating high-nitrate wastewater.
Scientific Reports, 5:8605 (2015)Impacts of the Three Gorges Dam on microbial structure and potential function.
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