Transcriptome and Metabolome Integration Analysis

Introduction

Transcriptome is an important method to obtain gene expression in organisms, and metabolome is the basis and direct manifestation of organism phenotype. Transcriptome sequencing can obtain a large number of differentially expressed genes and regulatory metabolic pathways, but it is difficult to associate genes and phenotypes, which makes it difficult to determine the key signal pathways, and therefore often fails to achieve the expected research goals. Metabolites are the final result of gene transcription under internal and external regulation of organisms, and are the material basis of organism phenotypes.

In the era of systems biology research, biological processes are complex and changeable, and gene regulatory networks are complex. For specific physiology, pathology and phenotypes research, transcriptome data are analyzed to obtain a large number of differentially expressed genes, and perform integration analysis with differential metabolites detected by metabolome, so as to understand the inner body of the organism from the two levels of cause and effect. For example, identify key gene targets, metabolites and metabolic pathways, build a core regulatory network, systematically and comprehensively analyze the complex mechanisms of disease occurrence and development, and explain biological problems as a whole. At present, the integration analysis of transcriptome and metabolome has been widely used in various disease research.

Fig 1. An overview workflow of the comprehensive analysis of metabolomics and transcriptomics in cervical cancer. (Yang K, et al. 2017)

What We Offer

As one of the experienced bioinformatics analysis service providers, we offer established, cost-efficient and rapid turnaround analysis services for transcriptome and metabolome integration analysis. The raw input transcriptome and metabolome data can be produced from a range of platforms including 10X Genomics, DropSeq etc. In addition, We can use various formats of data for analysis such as raw FastQ/Fasta files, or aligned BAM/SAM files and other intermediate data formats. We provide our clients with the following data analysis services：

• Professional data analysts evaluate and filter the data, formulate the optimal analysis plan, and perform data analysis.
• According to the analysis needs of customers, develop a personalized analysis plan, or develop a personalized chart summarizing the result.
• Provide a complete interactive data analysis report, including all analysis methods and results.
• Post-report follow-ups: We provide professional analysis report interpretation service and biological interpretation of analysis results.
• Fast turnaround time: we help you achieve your research goals quickly and in a timely manner.

Data Analysis Technical Route

Fig 2. Flow chart showing transcriptome and metabolome integration analysis.

Analysis Content Includes:

• Quality control evaluation of raw data (such as remove adapter and filter low-quality reads), including transcriptome data and metabolome data.
• Map to reference genome and or quantification using standard bioinformatics tools.
• Differential gene expression analysis and differential metabolite analysis, and draw a visual chart.
• Transcriptome and metabolome integration analysis.
• Draw a heat map of the correlation between differential genes and metabolites.
• Extract pathway information from Kyoto Encyclopedia of Genes and Genomes.
• Use cytoscape to draw a network diagram of the correlation between differential genes and differential metabolites.
• Conduct CCA and O2PLS analysis.
• Screen the final candidate biological target, mRNA or metabolite.

Data Ready

Before data analysis, the first thing is to get your data ready. The input data can be obtained from the following channels：

In order to process data more efficiently, we prefer to receive data files in the raw format, but we can also accept pre-normalized files.

What’s More

For transcriptome and metabolome integration analysis, if you don't have the raw data, CD Genomics can help by arranging for the generation of your data. We also have a variety of sequencing platforms, including PacBio, Nanopore, Illumina, and Miseq, etc. Alternatively, we are able to provide services for obtaining and mining data from available databases. In short, we are happy to work with you at every stage of your research to ensure the best outcome for your study. For transcriptome and metabolome integration analysis, if you have any questions, please feel free to contact us for details.

References

1. Yang K, et al. A Comprehensive Analysis of Metabolomics and Transcriptomics in Cervical Cancer[J]. Scientific Reports, 2017, 7:43353.
2. Nan J, et al. Identification of metabolic vulnerabilities of receptor tyrosine kinases-driven cancer[J]. NATURE COMMUNICATIONS, (2019) 10:2701.

* For research use only. Not for use in clinical diagnosis or treatment of humans or animals.