The Common Fund's Genotype-Tissue Expression (GTEx) program is providing valuable insights into the mechanisms of gene regulation by studying human gene expression and regulation in multiple tissues from health individuals; exploring disease-related perturbations in a variety of human diseases; and examining sexual dimorphisms in gene expression and regulation in multiple tissues. Genetic variation between individuals – underlying the many differences in gene expression – will be examined for correlation with differences in gene expression level to identify regions of the genome that influence whether and how much a gene is expressed. Identifying unique genomic variations associated with gene expression is expected to stimulate research towards understanding the genetic basis of complex diseases.
The GTEx project includes the following initiatives:
- Online data resource (GTEx Portal) for storing, cataloging, searching, and sharing aggregated level data
- Novel Statistical Methods for Human Gene Expression Quantitative Trait Loci (eQTL) Analysis
- Laboratory, Data Analysis, and Coordinating Center (LDACC) for acquiring and analyzing DNA and RNA from multiple human tissues
- Enhanced GTEx projects: including additional dimensions beyond gene expression to the GTEx data
GTEx dataset making a splash in evolutionary genetics
Following modern humans exodus from Africa ~60,000 years ago they encountered now-extinct Neandertals and on at least a few occasions interbreeding occurred. As a result, genomes of modern Eurasians contain ~1.5 to 4% Neandertal DNA. However, the contribution(s) of this DNA to modern human’s physiology and disease susceptibility/progression is only beginning to be understood. In a recent Science publication, Simonti and coworkers identified two single nucleotide polymorphisms (SNP) within the introgressed Neandertal DNA that were associated with disease. A SNP in the intron of P-selectin (SELP) was associated with a hypercoagulable state while a second upstream of stromal interaction molecule 1 (STIM1) was associated with incontinence, bladder pain, and urinary tract disorders. Because of the GTEx dataset they were able to show that both Neandertal SNPs are associated with changes in SELP (increased) and STIM1 (decreased) gene expression, suggesting that the effects from modern human-Neandertal interbreeding are still with us today.
Read the original research article (institutional subscription may be required for full text).
GTEx hopes to play a major role in uncovering genetic loci contributing to psychiatric disorders
Genome wide association studies (GWAS) have identified over 100 genetic loci associated with schizophrenia diagnosis. However, GWAS studies have limited ability to uncover how genetic loci associated with schizophrenia diagnosis alter biological processes resulting in risk for or protection from schizophrenia or whether those genetic loci associated with schizophrenia diagnosis are amenable to interventions. The GTEx program is optimistic that its sequence database containing over 900 post-mortem donors – over 420 of them whole brain donors – will help to untangle how the over 100 loci associated with schizophrenia diagnosis actually function in the progression of the disease. This week, a highly publicized Nature paper uncovered the biological basis for why the major histocompatibility complex locus, a GWAS-identified genetic loci spanning several megabases, is associated with schizophrenia diagnosis. With the aid of GTEx data from brain frontal cortex, the researchers showed that each common complement component 4A (C4A) allele associates with schizophrenia in proportion to its tendency to generate greater expression of C4A mRNA.
GTEx Perspective: Understanding how non-coding genomic polymorphisms affect gene expression
Read the Nature paper
Read a Washington Post article on the Nature paper
Correlations between genotype and tissue-specific gene expression levels will help identify regions of the genome that influence whether and how much a gene is expressed.Top: DNA and RNA is collected and analyzed from multiple tissues. Each donor has different genetic variants. In this example they are G/G, A/G, and A/A. Middle: Gene expression levels (RNA) are measured in each tissue from each individual and correlated with that individual’s genotype. Each donor has different gene expression (RNA) levels. In this example donor 1 has the highest while donor 3 has the lowest RNA levels in brain. Donor 2 is in the middle. RNA expression levels are treated as quantitative traits or expression quantitative trait loci (eQTLs). When eQTLs are correlated with genetic variation new genetic variants associated with, and potentially causal to, gene expression are discovered. In this example the genetic variant G/G is associated with high gene expression in brain while the genetic variant A/A is associated with low gene expression in brain. The genetic variant A/G is associated with intermediate gene expression in brain. When eQTLs between healthy and unhealthy individuals are compared, novel genes contributing to disease can be discovered. Bottom: The eQTL data and the donor tissues are deposited in the GTEx Portal and tissue repository for use by the scientific community.