Using the latest sequencing technologies and bioinformatic tools, our Metatranscriptomics service enables you to study microbial community dynamics, from soil and water to the human gut microbiome, from identifying active members of a community to characterizing microbial responses to environmental stressors.

Overview of Metatranscriptomics

The past few decades have seen significant advancements in sequencing technologies that have transformed how we conduct biological experiments, particularly when it comes to the study of complex microbiomes. Metatranscriptomics is a method to obtain deeper insights into how a microbial community responds over time to its changing environmental conditions. Often, RNA (cDNA) and DNA from the same community will be jointly extracted and sequenced in parallel, allowing for more flexible and accurate analyses later on. In terms of applications, Metatranscriptomics has been used to characterize active microbes in a community, discover novel microbial interactions, detect regulatory antisense RNA, track the expression of genes and determine the relationship between viruses and their host.

Fig1 Metatranscriptomics laboratory protocols, sequencing, and analysis. (Zhang, 2021)

Project Workflow

Data analysis

• De Novo Assembly
• Transcript Taxonomy
• Functional Annotation
• Enrichment Analysis
• Differential Expression Analyses

Sample Requirements

RNA sample quantity ≥ 5 μg. A260/280 ≥ 1.8, 28S:18S ≥ 1.5, RIN ≥ 7.

Deliverable: FastQ, BAM, coverage summary, QC report, taxonomic analysis, gene functional annotation, functional comparison, custom bioinformatics analysis.

References:

1. Zhang, Yancong, et al. Metatranscriptomics for the human microbiome and microbial community functional profiling. Annual Review of Biomedical Data Science 4 (2021): 279-311.
2. Mukherjee, Arkadeep, et al. Metatranscriptomics: an approach for retrieving novel eukaryotic genes from polluted and related environments. 3 Biotech 10.2 (2020): 1-19.
3. Shakya, Migun, et al. Advances and challenges in metatranscriptomic analysis. Frontiers in genetics 10 (2019): 904.