From personal genome to personal transcriptome
Genome analysis reveals how the DNA sequences that make up individual genes differ between individuals, which may contribute to differences in disease risk. However, it remains extremely challenging to accurately predict how any particular DNA change might affect biological function, limiting the clinical interpretation of genetic findings.
In a paper published on May 8th in the journal Science, Manuel Rivas and colleagues at Wellcome Trust Centre for Human Genetics in Oxford, together with Matti Pirinen (Institute for Molecular Medicine Finland FIMM), Daniel MacArthur (Broad Institute, US), Tuuli Lappalainen (New York Genome Center, US), and collaborators from the Genotype Tissue Expression (GTEx) Consortium, have measured the cellular effects of genetic variants in unprecedented depth.
They documented the impact on gene expression levels of variants that had a high probability of causing proteins to be missing or incomplete. These protein-truncating variants (PTVs) are often associated with disease, but may also have no obvious effect or even be beneficial. Cells have a protective mechanism against truncated proteins called ‘nonsense-mediated decay’ (NMD), which can degrade abnormal RNA messages before they are translated to proteins.
This decay phenomenon, and changes in the content of the RNA message can be detected from RNA sequencing data that the team analyzed. Matti Pirinen, who works as a Postdoctoral Researcher at FIMM, developed the statistical method used for analyzing the RNA sequence data. By utilizing this statistical package the team was able to compare the expression levels of the two different gene copies and thus make conclusions about the effect of the PTVs on gene expression. The method has just been published in the journal Bioinformatics.
As they report in the journal Science, Rivas, Pirinen, MacArthur, Lappalainen and their colleagues took advantage of two large-scale cohort studies that between them had sequenced both DNA and RNA from 635 individuals in order to uncover the functional effects of PTVs. The Geuvadis study combined genome sequencing data to RNA sequencing from cultured white blood cells, while the GTEx projects analyzed DNA sequences and expression data from multiple tissues from the same individuals.
In total the researchers identified 16,286 candidate PTVs. They were able to document that in almost 20 per cent of cases the effect of a PTV was specific to one or a subset of tissues. They also established that where a PTV knocked out expression in one of a pair of alleles, the complementary undamaged allele did not increase its expression to compensate – suggesting that in many cases, the ability of humans to tolerate the loss of one copy of a gene is driven by complex buffering processes rather than simply increasing expression of the remaining copy.
“We are able to go beyond DNA sequence alone and begin to understand the cellular consequences of this important class of genetic variation,” says Lappalainen. “This work shows how ‘personal transcriptomics’ – measuring gene expression in individuals – could become an important complement to genome analysis in the clinic, improving our diagnosis of a wide range of rare diseases,” concludes MacArthur.
Manuel A. Rivas, Matti Pirinen, Donald F. Conrad, Monkol Lek, et al., Effect of predicted protein-truncating genetic variants on the human transcriptome. Science, Vol. 348 no. 6235, pp. 666-669. 2015.
Matti Pirinen, Tuuli Lappalainen, Noah A. Zaitlen, GTEx Consortium, Emmanouil T. Dermitzakis, Peter Donnelly, Mark I. McCarthy and Manuel A. Rivas, Assessing allele-specific expression across multiple tissues from RNA-seq read data. Bioinformatics, 2015.
(Based on the press release from the Wellcome Trust Centre for Human Genetics, University of Oxford.)