Systems Genetics Approaches in Rat Identify Novel Genes and Gene Networks Associated With Cardiac Conduction

Author:

Adriaens Michiel E.12,Lodder Elisabeth M.1,Moreno‐Moral Aida3,Šilhavý Jan4,Heinig Matthias5,Glinge Charlotte1,Belterman Charly1,Wolswinkel Rianne1,Petretto Enrico63,Pravenec Michal4,Remme Carol Ann1,Bezzina Connie R.1

Affiliation:

1. Department of Experimental Cardiology Heart Centre Academic Medical Center Amsterdam Amsterdam The Netherlands

2. Maastricht Centre for Systems Biology Maastricht University Maastricht The Netherlands

3. Duke‐NUS Medical School Singapore

4. Institute of Physiology Academy of Sciences of the Czech Republic Prague Czech Republic

5. Institute of Computational Biology Helmholtz Zentrum München München Germany

6. The MRC London Institute of Medical Sciences Imperial College London London United Kingdom

Abstract

Background Electrocardiographic ( ECG ) parameters are regarded as intermediate phenotypes of cardiac arrhythmias. Insight into the genetic underpinnings of these parameters is expected to contribute to the understanding of cardiac arrhythmia mechanisms. Here we used HXB / BXH recombinant inbred rat strains to uncover genetic loci and candidate genes modulating ECG parameters. Methods and Results RR interval, PR interval, QRS duration, and QT c interval were measured from ECG s obtained in 6 male rats from each of the 29 available HXB / BXH recombinant inbred strains. Genes at loci displaying significant quantitative trait loci (QTL) effects were prioritized by assessing the presence of protein‐altering variants, and by assessment of cis expression QTL ( eQTL ) effects and correlation of transcript abundance to the respective trait in the heart. Cardiac RNA ‐seq data were additionally used to generate gene co‐expression networks. QTL analysis of ECG parameters identified 2 QTL for PR interval, respectively, on chromosomes 10 and 17. At the chromosome 10 QTL , ciseQTL effects were identified for Acbd4 , Cd300lg , Fam171a2 , and Arhgap27 ; the transcript abundance in the heart of these 4 genes was correlated with PR interval. At the chromosome 17 QTL , a ciseQTL was uncovered for Nhlrc1 candidate gene; the transcript abundance of this gene was also correlated with PR interval. Co‐expression analysis furthermore identified 50 gene networks, 6 of which were correlated with PR interval or QRS duration, both parameters of cardiac conduction. Conclusions These newly identified genetic loci and gene networks associated with the ECG parameters of cardiac conduction provide a starting point for future studies with the potential of identifying novel mechanisms underlying cardiac electrical function.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Cardiology and Cardiovascular Medicine

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