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Metatranscriptomics


Our Metranscriptomics platform elucidates three aspects of a microbial community, including gene activity diversity, gene expression abundance, and differential gene expression analysis by utilizing the most advanced next and third generation sequencing technologies and integrated bioinformatics analysis. The gene expression analysis can tell which genes exhibit the highest change in expression levels in different conditions to identify potential biomarkers and expression signatures.

Our Advantages:
  • Reveals the true extent of microbial diversity
  • Cost-efficient, wide coverage, and short cycle
  • Workflow automation: commercial kits, cutting-edge instruments, and integrated bioinformatics analysis pipeline
  • A wide range of applications, including basic research, ecological applications, environmental monitoring, clinical applications, industrial applications, and so on.
  • Analyzes the dynamic changes of microbial flora in all directions
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Introduction to Our Metatranscriptomics Platform

Metatranscriptomics is the study of the function and activity of the complete set of transcripts from environmental samples. It reveals the transcripts of metagenomes and the rule of transcriptional regulation in certain circumstances, and/or certain period at a holistic level. One significant advantage of metatranscriptomics is the avoidance of isolation and culture of certain microbial species, which effectively expand the available space of resources.

Metatranscriptomics Workflow

Our workflow for metatranscriptomics studies generally includes four parts: sample preparation, library preparation, high-throughput sequencing, and integrated bioinformatics analysis. We have a wide range of sequencing platforms, including Sanger sequencing, Illumina MiSeq/HiSeq, Roche 454, and PacBio SMRT sequencing systems. The appropriate sequencing strategies are determined based on your sample type and research purpose. Comprehensive and custom bioinformatics analyses are conducted by our experienced expert team.

Bioinformatics Analysis

The raw data of sequencing will have a certain proportion of low-quality data. So, the raw data need to be pre-processed to obtain clean data. Our bioinformatics Analysis primarily includes functional annotation, expression analysis, taxonomic analysis, enrichment analysis, comparative analysis.

Bioinformatics analysis Problems to be solved
Raw data preprocessing Filter low-quality data and remove adapter sequence to get clean data
Expression analysis Gene expression profiling of a certain population
Enrichment analysis KEGG pathway Gene-enriched signaling pathway, linking genomic information with higher order functional information.
GO analysis Gene product annotations in the areas of molecular function, biological process and cellular component
eggNOG/COG Annotation of orthologous groups of genes, prediction of evolutionary genealogy of genes
Multi-sample comparative analysis Clustering Discover classifications within complex data sets
PCoA Differences in functional distribution between different samples, explore the functional composition of multiple samples
Functional comparison
Correlation analysis Network analysis Study the relationships between microbes and environmental factors
CCA

Sample Requirement

Deliverables: raw sequencing data (FASTQ), clean data, trimmed and stitched sequences (FASTA), quality-control dashboard, sample contamination report, statistic data, and your designated bioinformatics result report.

Areas of Interest

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