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
,
cis
‐
eQTL
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
cis
‐
eQTL
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
Cited by
14 articles.
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