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Studies Elucidate Impact of Genetic Variants on Gene Expression in Human Tissues

NEW YORK (GenomeWeb) - Members of the Genotype-Tissue Expression (GTEx) consortium have published a collection of studies outlining results from a years-long effort to tease out the impact of genetic variants on gene expression in human tissues.

For the first of the studies, published online today in Nature, GTEx investigators gave an overview of genetic variant-gene expression relationships based on data from GTEx version 6p, spanning nearly four dozen human tissue types or cell lines from 449 individuals — an expression quantitative trait locus (eQTL) resource they mined for insights into cis- and trans-eQTL contributions to tissue-specific functions, disease risk, and more.

The team centered its analyses on genotyping and RNA sequence data from more than 7,000 postmortem samples, along with exome sequence data for all of the donors, and whole-genome sequence data for 148 individuals. The tissues in question included 31 solid organ tissue types, 10 sub-regions of the human brain, whole blood samples, and cell lines generated from blood and skin samples, the authors explained.

They noted that each tissue considered in the analysis was represented with samples from at least 70 donors. The GTEx team also compiled clinical information and histological features associated with these samples, along with the genotype and gene expression profiles.

The data "provide the deepest survey of individual- and tissue-specific gene expression to date," corresponding authors at Johns Hopkins University, the University of Pennsylvania, Princeton University, and Stanford University, and their colleagues wrote, "enabling a comprehensive view of the impact of genetic variation on gene expression levels."

For example, the researchers found that local eQTLs influencing nearby gene expression were widespread in the 44 tissue types or cell lines considered. There, they identified nearly 153,000 cis-eQTLs influencing the expression of 19,725 genes. The work also highlighted 112 eQTL loci with between-chromosome effects on the expression of at least 93 genes.

The team went on to assess everything from allele-specific expression and tissue-specific eQTL use to overlap between detected eQTLs and variants implicated in prior genome-wide association studies of cancer and other complex diseases.

For another Nature study, Stanford's Stephen Montgomery and Johns Hopkins' Alexis Battle led a team that used GTEx version 6p data to characterize rare variants influencing gene expression across the same 44 tissues. By focusing on genes with pronounced expression shifts in tissues from one or a few donors, they narrowed in on rare variants near more than half of the under-expressed genes and almost 30 percent of the genes with notably enhanced expression.

"Overall, we demonstrate that rare variants contribute to large gene expression changes across tissues and provide an integrative method for interpretation of rare variants in individual genomes," Montgomery, Battle, and their co-authors wrote.

Based on the patterns they identified, the investigators also established a statistical method known as "RNA-informed variant effect on regulation" (RIVER) that is designed to predict the regulatory impact of rare variants.

For their part, members of a Massachusetts General Hospital- and Broad Institute-led team took a look at X chromosome inactivation patterns in 29 tissue types, using high-coverage RNA sequence data for more than 5,500 GTEx samples and single-cell transcriptome data for 940 immune-related cells from four women.

Expanding from past studies pointing to expression of a significant proportion of genes from inactivated X chromosomes in females, they tabulated X inactivation escape by comparing expression of hundreds of X chromosome genes in diverse tissue samples from male and female GTEx participants. For nearly one-quarter of the X chromosome genes considered, they saw incomplete X chromosome inactivation, contributing to phenotypic diversity and expression differences between males and females.

"As a whole, these results highlight the between-female and male-female diversity introduced by incomplete [X chromosome inactivation]," the authors of that study wrote, noting that the "biological implications of [this finding] remain to be fully explored."

For their analysis of mammalian RNA editing dynamics, meanwhile, researchers from the US, Singapore, and elsewhere turned to RNA sequence data for more than 8,500 GTEx samples, representing 552 individuals and 53 tissue types or body sites. They also folded in transcript data for hundreds more primate or mouse samples in an effort to tease out the timing and distribution of a post-transcriptional process that swaps inosine in for adenosine at sites in RNA transcripts with the help of ADAR enzymes.

"We have demarcated major editing trends across tissues and over development and highlighted key differences in editing between human, non-human primates, and mouse," that study's senior author Jin Billy Li, a genetics researcher at Stanford, and his colleagues concluded.

Finally, for an accompanying Nature Genetics commentary, investigators from Stanford, the Broad, Massachusetts Institute of Technology, and the University of Chicago outlined the goals for a related project that has been underway since 2013. The "Enhancing GTEx" effort aims to expand information gleaned from GTEx samples by folding in other molecular profiles — from DNA or RNA methylation patterns to chromatin interaction and occupancy maps.

That project "extends the GTEx project to combine gene expression with additional intermediate molecular measurements on the same tissues to provide a resource for studying how genetic differences cascade through molecular phenotypes to impact human health," the authors of that article explained.

The original GTEx project, which kicked off in 2010, has already compiled data on 53 tissue types from more than 700 donors, as summarized in a version 7 release on the GTEx Portal. Raw data from the project has also been submitted to dbGAP, GTEx investigators noted. Results from the pilot stage of GTEx were reported in a handful of Science studies in 2015.

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