Premium
Dissection of Z‐disc myopalladin gene network involved in the development of restrictive cardiomyopathy using system genetics approach
Author(s) -
Lu Lu,
Gu Qingqing,
Mendsaikhan Uzmee,
Khuchua Zaza,
Jones Byron,
Towbin Jeffrey,
Purevjav Enkhsaikhan
Publication year - 2017
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.31.1_supplement.927.1
Subject(s) - genetics , biology , gene , locus (genetics) , expression quantitative trait loci , phenotype , candidate gene , quantitative trait locus , genotype , single nucleotide polymorphism
Background Genetic differences mediate individual differences in susceptibility to cardiomyopathy and severity of disease symptoms. Myopalladin ( Mypn ) is one of the genes associated with familial cardiomyopathies including dilated, hypertrophic and restrictive cardiomyopathy (RCM). Mutant knock‐in mice carrying the human Q529X ‐ MYPN mutation recapitulate the RCM phenotype the same as seen in the patients. The aim of this study was to investigate the regulation of Mypn and identify gene networks involved in RCM development. 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 proteomic data was 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 gene pathway and evaluate co‐expression networks. Results We found a wide range of expression variation in Mypn among the large cohort of BXD RI strains. Two upstream genetic loci, modulators of the expression of Mypn, have been identified on chromosomes 1 and 5. Candidate genes within those loci include Ncoa2, Vcpip1, Sgk3, and Lgi2 . We also identified 15 sarcomeric genes that interact with Mypn , and constructed the Mypn gene network. Among them, well‐known cardiomyopathy‐associated genes such as Ldb3, Des, Actn2, Fhod3, Tpm2, and Syne1 were found to be members of this network. Several novel genes ( Myo18b, Fhod3, Myom1, Bmp10, Myl4, Obscn, and Pdlim5 ) were also related to the Mypn network. In particular, two members ( Syne1 and Myom1 ) have been confirmed at the protein level as high chance genes working as modifiers to induce cardiomyopathy. Conclusions Through a systematic genetic strategy we found several novel genes interacting with Mypn that may play an important role in the development of RCM. This work demonstrates that a systematic genetics approach is a powerful tool for constructing co‐expression networks that define the biological process categories within which similarly regulated genes function. Support or Funding Information R01HL128350 (Lu L), R01 HL53392 and R01 HL087000 (Towbin JA)