The occurrence and development of disease or cancer involves complex biological processes. The combination of extensive targeted metabonomics and Transcriptomics, combined with molecular biology technology, can explore the mechanism of tumor physiological and pathological response in a more comprehensive way. We integrated and analyzed many tumor genes expressed in time series and differentially accumulated tumor metabolite information, and combined the two data through KEGG metabolic pathway. Finding the genes and metabolites that participate in the significant changes in (KEGG Pathway) in the same biological process can quickly lock on the key genes.
Figure 1. Flow chart of correlation analysis between Transcriptomics and metabonomics
The purpose of our research
Tumor Transcriptomics sequencing can obtain a large number of differentially expressed genes and regulate metabolic pathways, but because the genes and phenotypes are difficult to correlate, the key signaling pathways are difficult to determine, so they often fail to achieve the intended research goals. We focus on specific tumor phenotypes and use a combination of extensively targeted metabolomics and transcriptomics research methods to integrate the analysis of many genes expressed in time series and differentially accumulated metabolite information. Explain the biological phenotype of interest at a level, and explore the growth and development of the organism and the physiological and pathological response mechanism.
We use the KEGG metabolic pathway to combine metabolomics and transcriptomics data to find genes and metabolites involved in significant changes in the same biological process, which can quickly target key genes.
Comprehensive data: use comprehensive Transcriptomics data and the latest metabolome database to analyze the interrelationship between Transcriptomics and metabolome throughout the year
Association analysis: Integrate Transcriptomics and metabolomics data, dig deep into genes and metabolites involved in the regulatory process, and reveal the true gene expression regulatory network
Rich project experience: It has a mature research portfolio plan to help users quickly publish research results
Transcriptomics sequencing samples:
Tumor cells, tissues, whole blood, serum, plasma, total RNA, etc.
Recommended starting amount of total RNA: 2 μg, minimum 1μg, concentration ≥ 50 ng /μL.
Metabolome analysis samples:
Tumor cells, tissues, urine, whole blood, serum, plasma, etc.
Recommended starting amount (single): plasma or serum > 300μL, urine > 5 mL, tissue> 100 mg, and cells > 107.
Sampling Kit: we provide our customers with a complete sampling kit, including protein and RNA separation kits, as well as tools for storing samples.
Deliverables: raw sequencing data, pruning and stitching sequences, quality control report results, statistics and bioinformatics reports you specify, visual pictures.
Please contact us to find out how we can help you achieve the next research breakthrough.