Gene expression levels are an important intermediary between DNA variation and higher-order complex phenotypes. In the past few years, genome-wide association studies (GWAS) of gene expression have identified genetic variants associated with transcript abundance for many genes. The existence of eQTL databases containing catalogs of eQTLs has helped to interpret findings from genome-wide association studies, identifying new genes for childhood asthma, Crohn’s disease, Type 1 diabetes, Graves’ disease, human height, body-mass index, waist-hip ratio, osteoporosis-related traits and many others. EQTLs have also been successfully used to prioritize SNPs genotyped in GWAS to identify relevant pathways for complex diseases. The development and utility of eQTL mapping has become an exciting research direction in the study of the genetics of complex diseases. A Research Topic focusing on this area is likely to boost research in this area, promote international collaboration from different disciplines, provide a big picture overview of future directions, and eventually lead to profound impact on the genetics of complex diseases and traits.
The aim of this Research Topic is to bring together researchers in this community to present the cutting-edge advancement in this area and prosper its future agenda. To maximize its benefit to the reader community, the scope of this Research Topic should include all related areas of research, theories, opinion, methods, areas of impact, and historical review. Some example topics include, but are not limited to:
* Novel methods or applications for eQTL mapping
* Novel methods or applications to integrate external eQTL database with past or ongoing candidate gene or genome-wide association studies
* Novel methods or applications for datasets where genetic data, gene expression and phenotype information are available on the same subjects
* Disease mapping studies using eQTL information
* Opinion on current and future studies involving eQTL
* EQTL studies involving different techniques, especially high throughput techniques such as microarray and RNA-seq
* Novel methods or applications for discerning the tissue- or population-specificity of eQTLs
* Novel methods or applications for perturbation/response QTLs
* EQTL database/browser development and integration of multiple databases
* Review article for the history, current advancement and future directions
Mapping complex disease traits with global gene expression has shown to be an important strategy in genetics of complex diseases and traits. Geneticists are keen to know how best to use gene expression data to interpret genetic variants identified from genetic studies and how to use this external information to improve power of genome-wide association studies. A Research Topic in this area will be appreciated by readers interested in disease mapping and welcomed by researchers in the community. Besides gene expression, genetic maps of DNA methylation variation share similar methodology and utility as eQTL maps, thus methods and applications for associating genetic variation with DNA methylation may also be included in this Research Topic.
Gene expression levels are an important intermediary between DNA variation and higher-order complex phenotypes. In the past few years, genome-wide association studies (GWAS) of gene expression have identified genetic variants associated with transcript abundance for many genes. The existence of eQTL databases containing catalogs of eQTLs has helped to interpret findings from genome-wide association studies, identifying new genes for childhood asthma, Crohn’s disease, Type 1 diabetes, Graves’ disease, human height, body-mass index, waist-hip ratio, osteoporosis-related traits and many others. EQTLs have also been successfully used to prioritize SNPs genotyped in GWAS to identify relevant pathways for complex diseases. The development and utility of eQTL mapping has become an exciting research direction in the study of the genetics of complex diseases. A Research Topic focusing on this area is likely to boost research in this area, promote international collaboration from different disciplines, provide a big picture overview of future directions, and eventually lead to profound impact on the genetics of complex diseases and traits.
The aim of this Research Topic is to bring together researchers in this community to present the cutting-edge advancement in this area and prosper its future agenda. To maximize its benefit to the reader community, the scope of this Research Topic should include all related areas of research, theories, opinion, methods, areas of impact, and historical review. Some example topics include, but are not limited to:
* Novel methods or applications for eQTL mapping
* Novel methods or applications to integrate external eQTL database with past or ongoing candidate gene or genome-wide association studies
* Novel methods or applications for datasets where genetic data, gene expression and phenotype information are available on the same subjects
* Disease mapping studies using eQTL information
* Opinion on current and future studies involving eQTL
* EQTL studies involving different techniques, especially high throughput techniques such as microarray and RNA-seq
* Novel methods or applications for discerning the tissue- or population-specificity of eQTLs
* Novel methods or applications for perturbation/response QTLs
* EQTL database/browser development and integration of multiple databases
* Review article for the history, current advancement and future directions
Mapping complex disease traits with global gene expression has shown to be an important strategy in genetics of complex diseases and traits. Geneticists are keen to know how best to use gene expression data to interpret genetic variants identified from genetic studies and how to use this external information to improve power of genome-wide association studies. A Research Topic in this area will be appreciated by readers interested in disease mapping and welcomed by researchers in the community. Besides gene expression, genetic maps of DNA methylation variation share similar methodology and utility as eQTL maps, thus methods and applications for associating genetic variation with DNA methylation may also be included in this Research Topic.
