Dissection of Z-disc myopalladin gene network involved in the development of restrictive cardiomyopathy using system genetics approach

doi:10.4330/wjc.v9.i4.320

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World Journal of Cardiology

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World J Cardiol. Apr 26, 2017; 9(4): 320-331
Published online Apr 26, 2017. doi: 10.4330/wjc.v9.i4.320

Dissection of Z-disc myopalladin gene network involved in the development of restrictive cardiomyopathy using system genetics approach

Qingqing Gu, Uzmee Mendsaikhan, Zaza Khuchua, Byron C Jones, Lu Lu, Jeffrey A Towbin, Biao Xu, Enkhsaikhan Purevjav

Qingqing Gu, Biao Xu, Department of Cardiology, Drum Tower Clinic Hospital, Nanjing Medical University, Nanjing 211166, Jiangsu Province, China

Qingqing Gu, Lu Lu, Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38103, United States

Uzmee Mendsaikhan, the Heart Institute, Cincinnati Children’s Hospital Medical Center and Mongolian National University of Medical Sciences, Ulaanbaatar 14210, Mongolia

Zaza Khuchua, the Heart Institute, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, United States

Byron C Jones, the Neuroscience Institute, Department of Genetics, Genomics and Informatics, University of Tennessee Health Science Center, Memphis, TN 38103, United States

Jeffrey A Towbin, Enkhsaikhan Purevjav, Department of Pediatrics, the Heart Institute, University of Tennessee Health Science Center, Memphis, TN 38103, United States

Jeffrey A Towbin, Enkhsaikhan Purevjav, Children’s Foundation Research Institute, Le Bonheur Children’s Hospital Memphis, TN 38103, United States

Jeffrey A Towbin, Pediatric Cardiology, St. Jude Children’s Research Hospital, Memphis, TN 38103, United States

Author contributions: Gu Q performed experiment and data analysis; Mendsaikhan U maintained animals, performed the in vivo experiments and proteomics analysis; Khuchua Z assisted in performing proteomics analysis; Xu B supported post-doc; Jones BC edited manuscript; Lu L performed data analysis and drafted manuscript; Towbin JA supervised all experimentation, edited and revised the manuscript; Xu B supported post-doc, designed experiment; Purevjav E acquired conception and design of the study, performed proteomics analysis and interpretation, drafted and edited the manuscript.

Supported by National Institutes of Health, Nos. R01 HL128350 (LL), R01 HL53392 and R01 HL087000 (JAT).

Institutional animal care and use committee statement: All animal studies were approved by institutional IACUC of the University of Tennessee Health Science Center (UTHSC).

Conflict-of-interest statement: To the best of our knowledge, no conflict of interest exists.

Data sharing statement: Resources: Principles and Guidelines for Recipients of NIH Grants and Contracts” issued in December, 1999. Dr. Lu Lu is responsible for coordinating data sharing through GeneNetwork (GN) at the: http://www.genenetwork.org/webqtl/main.py. GN is a group of linked data sets and tools used to study complex networks of genes, molecules, and higher order gene function and phenotypes. GN combines more than 25 years of legacy data generated by hundreds of scientists together with sequence data (SNPs) and massive transcriptome data sets (expression genetic or quantitative trait locus data sets). GN connected to numerous links to the UCSC and Ensembl Genome Browsers, PubMed, Entrez Gene, GNF Expression Atlas, ABI Panther, and WebGestalt provide users with rapid interpretive information about genomic regions, published phenotypes and genes.

Correspondence to: Enkhsaikhan Purevjav, MD, PhD, Department of Pediatrics, the Heart Institute, University of Tennessee Health Science Center, 71 S Manassas Street, Memphis, TN 38103, United States. epurevja@uthsc.edu

Telephone: +1-901-4481117 Fax: +1-901-2864551

Received: December 6, 2016
Peer-review started: December 7, 2016
First decision: January 16, 2017
Revised: February 9, 2017
Accepted: February 28, 2017
Article in press: March 2, 2017
Published online: April 26, 2017
Processing time: 143 Days and 2.2 Hours

Abstract

AIM

To investigate the regulation of Myopalladin (Mypn) and identify its gene network involved in restrictive cardiomyopathy (RCM).

METHODS

Gene expression values were measured in the heart of a large family of BXD recombinant inbred (RI) mice derived from C57BL/6J and DBA/2J. The proteomics data were collected from Mypn knock-in and knock-out mice. Expression quantitative trait locus (eQTL) mapping methods and gene enrichment analysis were used to identify Mypn regulation, gene pathway and co-expression networks.

RESULTS

A wide range of variation was found in expression of Mypn among BXD strains. We identified upstream genetic loci at chromosome 1 and 5 that modulate the expression of Mypn. Candidate genes within these loci include Ncoa2, Vcpip1, Sgk3, and Lgi2. We also identified 15 sarcomeric genes interacting with Mypn and constructed the gene network. Two novel members of this network (Syne1 and Myom1) have been confirmed at the protein level. Several members in this network are already known to relate to cardiomyopathy with some novel genes candidates that could be involved in RCM.

CONCLUSION

Using systematic genetics approach, we constructed Mypn co-expression networks that define the biological process categories within which similarly regulated genes function. Through this strategy we have found several novel genes that interact with Mypn that may play an important role in the development of RCM.

Keywords: System genetics; Myopalladin; System proteomics; Cardiomyopathy; Mutation

Core tip: Myopalladin (Mypn) is one of genes associated with many types of familial cardiomyopathies including dilated, hypertrophic and restrictive cardiomyopathy (RCM). Using systematic genetics approach, we constructed Mypn co-expression networks of similarly regulated genes that function within defined biological processes. Several novel Mypn-interacting genes with potential important role in the development of RCM were discovered.