CD Genomics offers efficient and cost-effective fast turnaround analysis services for a wide range of proteomics and transcriptomics data from various platforms, including labeled or unlabeled LC-MS/MS and protein immunoassays, as well as NGS and long-read sequencing data. We can accept data in various formats, such as peptide or protein-specific intensity and spectral count matrices, or combined miRNA and other small RNA data for analysis.
Introduction
Transcriptomics is an intermediate module that links the genome and proteome. It involves a complex set of expression regulation mechanisms, such as transcriptional regulation, post-transcriptional regulation, translation regulation, and post-translation regulation. Integrating transcriptomics and proteomics data through multi-omics analysis is beneficial for studying the multi-level regulation of gene expression, providing a panoramic view of gene expression, and offering more comprehensive information for medical research, drug development, and agricultural development.
Transcriptomics studies the function of the transcriptome in cells, tissues, or organisms under various biological conditions. The relationship between the transcriptome and the genome indicates that the information of the organism is stored in DNA (genome) and expressed through RNA (transcriptome). The main focus of transcriptomics is to discover how the transcriptome of cells, tissues, or organisms is affected by diseases or environmental factors such as drugs and hormones. Non-coding RNA is another essential aspect of transcriptomics. These functional elements play a vital role in the occurrence of various diseases and their response to treatment.
Proteomics is a high-throughput study of the protein composition of cells, tissues, organisms, or other biological systems. In addition to steady-state abundance, proteomics can also help determine the location and rate of specific protein production and degradation over time. Other proteomics techniques can identify post-translational modifications (PTMs), interactions, and movement between subcellular compartments.
Integrated proteomic and transcriptomic analysis
CD Genomics Data Analysis Pipeline
How Can We Help You
- Comprehensive analysis of gene and protein expression levels in a specific biological state, providing a panoramic view of the expression profile.
- Identification of key proteins or genes regulated after transcription, allowing the discovery of critical metabolic pathways or regulatory factors.
- Construction of a protein database from transcriptome data for species with incomplete protein databases, significantly improving protein identification numbers.
- Construction of a protein database from transcriptome sequencing for species with no reference genome, greatly increasing protein identification numbers.
- Correlation analysis of differential proteins and differential genes based on expression levels.
How It Works
Initial Consultation
- Discuss project design and scope of work
- Determine sample preparation and sequencing requirements
- Provide an estimated schedule and budget
Project Confirmation
- If you don't have data yet, we can also provide omics sequencing services
- Project confirmation process
Data Analysis
- Perform quality control and data filtering
- Align the reads to the reference genome
- Perform downstream analysis such as functional annotation, pathway analysis, or gene network analysis
Deliverables
- Compiles all data and determine the most appropriate statistical methods to provide a biological interpretation of the results.
- Provides technical support to help expand data analysis or design subsequent validation experiments.
Application
- Biomarker analysis: analysis of viral infection mechanisms and prediction of biomarkers
- Drug Action Evaluation: Study of changes in the proteome and transcriptome of cancer cells or tissues in various model organisms caused by drugs or knockouts
- Plant and animal growth and development research: analysis of biomolecular synthetic pathways for plant and animal growth and development
Reference
- Ichikawa H, Yoshida A, Kanda T, et al. Prognostic significance of promyelocytic leukemia expression in gastrointestinal stromal tumor; integrated proteomic and transcriptomic analysis. Cancer Science, 2015, 106(1): 115-124.
