Expression Quantitative Trait Loci Analysis

Expression Quantitative Trait Loci Analysis Online Inquiry

CD Genomics as one of the providers of expression quantitative trait loci analysis (eQTL analysis), we use bioinformatics to help you quickly study the correlation between genetic mutation and disease or phenotypic characteristics. Our unique data analysis skills and appropriate software tools can meet customers' personalized laboratory data analysis needs and provide you with easy-to-interpret data analysis reports.


The Expression Quantitative Trait Loci (eQTL) refers to some regions on the chromosome that can specifically regulate the expression levels of mRNA and protein. The expression level of mRNA / protein is proportional to the quantitative traits. The expression data of each genotype was regarded as a quantitative trait and analyzed using traditional QTL analysis methods. eQTL can be divided into cis eQTL and trans eQTL. The cis eQTL is the eQTL of a gene that maps to the genomic region where the gene is located, indicating that it may be caused by the difference in the gene itself to change the mRNA level, and the trans eQTL refers to the location of the eQTL of a gene to other genomic regions, indicating that differences in other genes control differences in mRNA levels of that gene.

The eQTL analysis can be applied to human genetics research. In the process of genetic research, some disease-causing or susceptible mutations are often found, but how these mutations cause phenotypic changes is not intuitive. Therefore, the differential expression of a gene is used as a transition, from gene mutation to gene expression change, and finally to phenotype. The specific principle of eQTL analysis is to use gene expression as a quantitative trait to study the correlation between genetic mutation and gene expression, so as to study the correlation between genetic mutation and disease or phenotypic characteristics.

eQTL analysis is a bridge between genetic changes and diseases. - CD GenomicsFig 1. eQTL analysis is a bridge between genetic changes and diseases.

Application of eQTL

Research on susceptibility sites of complex diseases.

Analysis of drug targets.

Population cohort study.

Advantages of eQTL Analysis

Using eQTL combined with GWAS analysis methods to find disease risk sites can be applied to complex disease research.

The eQTL analysis can explain the regulatory relationship between gene mutations in non-coding regions and gene expression. And systematically understand the regulatory mechanism of gene transcription and construct a gene expression regulatory network.

In population cohort studies, eQTL analysis can be used to compare eQTL differences in different populations, thereby enriching the results of population cohort studies, and finding the relationship between gene differences and gene expression regulation in different populations.

Performing eQTL difference analysis on the body or cells before and after drug treatment can well study the difference before and after drug treatment, and provide gene-level evidence for finding drug targets and drug action mechanisms.

CD Genomics Data Analysis Pipeline

The eQTL analysis process can be divided into two three steps:

Firstly, perform whole genome-wide association analysis to detect various mutations in the coding region and non-coding region, and perform association analysis to screen disease-causing or susceptible sites.

Secondly, the mRNA sequencing data is analyzed, and the mRNA expression level is analyzed to obtain information such as differential genes, variable splicing, and new transcripts.

Finally, eQTL analysis is performed, and the candidate pathogenic sites or susceptible sites obtained from the whole genome-wide association analysis and the expression information obtained from mRNA data analysis are subjected to eQTL analysis to further narrow the candidate pathogenic or susceptible sites information, and then establish the network relationship between gene mutation and expression regulation through various models, and explore the molecular mechanisms related to the occurrence and development of diseases.

The specific analysis content of eQTL is as follows

eQTL analysis process. - CD GenomicsFig 2. eQTL analysis process

Turnaround Time

eQTL analysis turnaround time - CD Genomics

About one to two weeks, it's related to the quality and data volume of genome-wide data and transcriptome data.

Bioinformatics-Analysis, a division of CD Genomics, provides eQTL analysis to help you study the correlation between genetic mutation and disease or phenotypic characteristics. Experienced teams of scientists, researchers, and technicians, we provide fast turnaround, high-quality data reports at competitive prices for worldwide customers. Customers can contact our employees directly and we will respond promptly. If you are interested in our services, please contact us for more detailed information.


  1. Xu Z, Wu C, et al. A Powerful Framework for Integrating eQTL and GWAS Summary Data[J]. Genetics, 2017:genetics.300270.2017.
* For Research Use Only. Not for use in diagnostic procedures.
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