Understanding how naturally occurring genetic variation affects gene expression levels is the first step in understanding complex traits at the molecular level. The Expression Quantitative Trait Locus (eQTL) mapping study attempts to locate all genomic regions that affect / associate gene expression levels through genotyping and determination of individual genome-wide expression levels.
In current small and medium gene expression studies, RNA-seq technology has almost replaced chip technology. However, large-scale gene expression research has been slow to embrace the next-generation sequencing. So far, almost all eQTL studies have mainly used chip technology to measure expression profiles.
Only two published articles use RNA-seq to study the genetics of human gene expression. The University of Chicago Pritchard research team used RNA-seq to identify the gene expression of 69 African HapMap samples, while another team from Europe analyzed 60 European HapMap samples. These two results were published in the 2010 "Nature" topic-Ten Years of the Human Genome Project. In fact, except for the ENCODE / MODENCODE project, no large-scale RNA-seq data is currently published. ENCODE published more than 410 RNA-seq studies, mainly from several cell lines, not population-level data.
People are also wondering why genetic research on gene expression is slow. There are of course many reasons, including funding, the scale of such research, the challenge of collecting genotypes from the same population, expression, and the difficulty of analyzing RNA-seq data. However, all this is expected to change soon. At the 2013 Genome Biology Conference held recently, two genetic studies on human gene expression used RNA-seq data. The European Geuvadis project uses some samples from the Thousands Genome Project to establish standards for biological / medical interpretation of sequence data related to clinical phenotypes. The Geuvadis project has sequenced mRNA and microRNA molecules from 465 lymphoblastoid cell line (LCL) samples from 5 populations. Of the five groups, one is from Africa (YRI) and the other four are from Europe (CEU, FIN, GBR and TSI). According to reports, Geuvadis has obtained RNA-seq and microRNA-seq data, and the research results will be published soon.
Another study, led by Stanford University ’s Alexis Battle, aimed to sequence transcriptomes of 922 individuals in the same group and genotype 737,187 common SNPs. This is by far the largest transcriptome sequencing study. They performed ultra-deep sequencing of mRNA from each individual's whole blood and obtained more than 60 million reads. In addition, NIH's Genotype-Tissue Expression (GTEx) program is also creating the largest genotype and gene expression resources. It performs RNA-seq analysis of 30-50 tissues in the human body, including brain, lung, heart and muscle. Researchers have obtained data from the experimental phase, including genotype data from 190 individuals and RNA-seq data from more than 1800 tissues. GTEx plans to gradually expand the sample size.
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