Genetic correlations reveal the shared genetic architecture of transcription in human peripheral blood

Samuel W. Lukowski, Luke R. Lloyd-Jones, Alexander Holloway, Holger Kirsten, Gibran Hemani, Jian Yang, Kerrin Small, Jing Zhao, Andres Metspalu, Emmanouil T. Dermitzakis, Greg Gibson, Timothy D. Spector, Joachim Thiery, Markus Scholz, Grant W. Montgomery, Tonu Esko, Peter M. Visscher and Joseph E. Powell ()
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Samuel W. Lukowski: University of Queensland
Luke R. Lloyd-Jones: University of Queensland
Alexander Holloway: University of Queensland
Holger Kirsten: University of Leipzig
Gibran Hemani: MRC Integrative Epidemiology Unit (IEU) at the University of Bristol
Jian Yang: University of Queensland
Kerrin Small: King’s College London
Jing Zhao: Georgia Institute of Technology
Andres Metspalu: University of Tartu
Emmanouil T. Dermitzakis: University of Geneva
Greg Gibson: Georgia Institute of Technology
Timothy D. Spector: King’s College London
Joachim Thiery: University of Leipzig
Markus Scholz: University of Leipzig
Grant W. Montgomery: University of Queensland
Tonu Esko: University of Tartu
Peter M. Visscher: University of Queensland
Joseph E. Powell: University of Queensland

Nature Communications, 2017, vol. 8, issue 1, 1-10

Abstract: Abstract Transcript co-expression is regulated by a combination of shared genetic and environmental factors. Here, we estimate the proportion of co-expression that is due to shared genetic variance. To do so, we estimated the genetic correlations between each pairwise combination of 2469 transcripts that are highly heritable and expressed in whole blood in 1748 unrelated individuals of European ancestry. We identify 556 pairs with a significant genetic correlation of which 77% are located on different chromosomes, and report 934 expression quantitative trait loci, identified in an independent cohort, with significant effects on both transcripts in a genetically correlated pair. We show significant enrichment for transcription factor control and physical proximity through chromatin interactions as possible mechanisms of shared genetic control. Finally, we construct networks of interconnected transcripts and identify their underlying biological functions. Using genetic correlations to investigate transcriptional co-regulation provides valuable insight into the nature of the underlying genetic architecture of gene regulation.

Date: 2017
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DOI: 10.1038/s41467-017-00473-z

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