Transcriptomics is the study of functional genomics, which is the study of the transcription and regulation of all genes in a cell at a holistic level. Transcriptomics can use all the information about gene expression regulation and protein function to solve biological problems. The purpose of transcriptomics is not only to study the changes in the expression level of each gene in different transcriptome samples, but also to determine the localization and annotation of the transcriptome and the function and structure of each gene in the genome.
Introduction of Transcriptomics and Metabolomics Analysis
Transcriptome studies identify key differentially expressed genes at the gene level to reveal intrinsic regulatory mechanisms. However, the transcriptome is difficult to correlate directly with the phenotype. CD Genomics' transcriptomics and metabolomics analysis can rapidly identify metabolism-related functional genes from a large number of transcripts, construct core regulatory networks, identify key candidate genes, and elucidate biological phenomena.
Figure 1. Flowchart of transcriptomics and metabolomics analysis in obese vs. non-obese BC patients. (Hassan MA, et al., 2020)
Our Routine Transcriptomics and Metabolomics Analysis Services Pipelines Include
Our transcriptome and metabolome services are based on the following three main ideas. First, a joint analysis using two independent omics data. Second, mutual validation using two omics data. Third, using the two omics data to determine the focus of the analysis, and then further analysis of the focus. All three ideas follow the following analysis process.
- Transcriptomics analysis. We first performed quality control processing of the raw data from the transcriptome libraries using filtering and data cleaning methods. Then, we choose different data analysis processes depending on whether a reference genome exists for your study species and whether new transcripts need to be analyzed for research purposes.
| Reference genome exists and new transcripts need to be analyzed | Reference genome matching |
| Transcript matching assembly | |
| Quantitative analysis of transcript expression | |
| Variance analysis and functional enrichment analysis | |
| Reference genome exists and known transcripts need to be analyzed | Transcript sequences matching |
| Quantitative analysis of transcript expression | |
| Variance analysis and functional enrichment analysis | |
| No reference genome exists | De novo assembly of transcript sequences |
| Quantitative analysis of transcript expression | |
| Variance analysis and functional enrichment analysis |
- Metabolomics analysis. The metabolomics data obtained from the assays are first preprocessed to filter low-quality data and normalize the data. We use principal component analysis to reduce the dimensionality of the metabolomic data to reveal the grouping, trend, and outlier information of the data in the dataset. Subsequently, differential metabolite analysis and metabolic pathway analysis are performed.
- Transcriptomics and metabolomics analysis. The methods of association analysis between transcriptome and metabolome mainly include KEGG pathway-based annotation and enrichment analysis, Pearson correlation analysis, and model building based on dimensionality reduction to determine association analysis.
Deliverables
We can provide the following analysis results, including but not limited to.
- Heat map of differential genes and differential metabolite pathways.
- Nine-quadrant diagram of the correlation between genes and metabolites.
- Network diagram of the correlation between differential genes and differential metabolites.
- Heat map of correlation clustering of differential genes with differential metabolites.
- Heat map of KEGG pathway enrichment analysis.
How Can We Help You
Choosing our transcriptomics and metabolomics analysis services can help you solve the following problems.
- Screening tumor markers. Screening for tumor markers. During cancer development, regulation of gene networks may allow changes in cancer cell-associated metabolic pathways, resulting in changes in the abundance of metabolite levels. We screen for possible markers for early diagnosis or prognosis of tumors by combining analysis of differentially expressed genes and metabolites.
- Metabolic engineering. Genome-wide transcriptional analysis can help researchers to more accurately assess cell phenotypes, as well as help researchers to identify target genes for strain improvement and accelerate the rational design and modification of microbial cell factories.
- Selection and breeding of superior plant varieties. We integrate transcriptomic data and metabolomic data of plants under environmental stresses such as low temperature and drought to analyze the response mechanisms of plants to environmental stresses and lay the foundation for the selection and breeding of resistant varieties.
Can CD Genomics help me generate raw data?
Yes, we can. With advanced instrumentation, a high-coverage self-built database, and experienced metabolomics experts, we can provide you with sequencing services and metabolite detection services.
How should I prepare and send my samples?
If you require our transcriptome sequencing and metabolomics testing services, please send samples as requested in the form below and contact us. If both transcriptome and metabolome testing services are required for the same sample, the sample should be split into two.
| Sample Type | Minimum requirement per sample | Storage and transportation |
|---|---|---|
| Serum, Plasma, cerebrospinal fluid | 200 ul | For LCMS Snap freeze in liquid nitrogen. Store at -80 ℃. Ship with dry ice. For RNAseq Immerse tissues in 5x RNAlater. Prepare whole blood with 3x Trizol Resuspend cells with 1ml TRIzol for every 5x106 cells. Snap-freeze materials in liquid nitrogen and store all materials at -80 ℃. |
| Whole blood | 2 ml | |
| Urine | 500 ul | |
| Tissue | 300 g | |
| Cultured Cells | 1 x 107 cells | |
| Fecal elements, intestinal contents | 1 g | |
| Rumen fluid, fermentation fluid, tissue fluid | 1 g of pellet | |
| Plant materials | 3 g |
Why combine transcriptomics and metabolomics analysis?
The transcriptome data can be used to obtain a large number of differentially expressed genes and regulate metabolic pathways, which can be correlated with the differential metabolites obtained from metabolomic assays to analyze the intrinsic changes of organisms at two levels. They can identify key gene targets, metabolites, and metabolic pathways, build core regulatory networks, systematically and comprehensively analyze the complex mechanisms of disease development, and explain biological problems from a holistic perspective.
References
- Hassan MA, et al. Integration of Transcriptome and Metabolome Provides Unique Insights to Pathways Associated With Obese Breast Cancer Patients. Front Oncol. 2020 May 19; 10: 804.
- Liu Z, et al. Integration of Transcriptome and Metabolome Reveals the Genes and Metabolites Involved in Bifidobacterium bifidum Biofilm Formation. Int J Mol Sci. 2021 Jul 15 ;22(14): 7596.
