Dataset Information

Genetic Variation in Enhancers Modifies Cardiomyopathy Gene Expression and Progression.

ABSTRACT:

Background

Inherited cardiomyopathy associates with a range of phenotypes, mediated by genetic and nongenetic factors. Noninherited cardiomyopathy also displays varying progression and outcomes. Expression of cardiomyopathy genes is under the regulatory control of promoters and enhancers, and human genetic variation in promoters and enhancers may contribute to this variability.

Methods

We superimposed epigenomic profiling from hearts and cardiomyocytes, including promoter-capture chromatin conformation information, to identify enhancers for 2 cardiomyopathy genes, MYH7 and LMNA. Enhancer function was validated in human cardiomyocytes derived from induced pluripotent stem cells. We also conducted a genome-wide search to ascertain genomic variation in enhancers positioned to alter cardiac expression and correlated one of these variants to cardiomyopathy progression using biobank data.

Results

Multiple enhancers were identified and validated for LMNA and MYH7, including a key enhancer that regulates the switch from MYH6 expression to MYH7 expression. Deletion of this enhancer resulted in a dose-dependent increase in MYH6 and faster contractile rate in engineered heart tissues. We searched for genomic variation in enhancer sequences across the genome, with a focus on nucleotide changes that create or interrupt transcription factor binding sites. The sequence variant, rs875908, disrupts a T-Box Transcription Factor 5 binding motif and maps to an enhancer region 2 kilobases from the transcriptional start site of MYH7. Gene editing to remove the enhancer that harbors this variant markedly reduced MYH7 expression in human cardiomyocytes. Using biobank-derived data, rs875908 associated with longitudinal echocardiographic features of cardiomyopathy.

Conclusions

Enhancers regulate cardiomyopathy gene expression, and genomic variation within these enhancer regions associates with cardiomyopathic progression over time. This integrated approach identified noncoding modifiers of cardiomyopathy and is applicable to other cardiac genes.

SUBMITTER: Gacita AM

PROVIDER: S-EPMC8009836 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Publications

Genetic Variation in Enhancers Modifies Cardiomyopathy Gene Expression and Progression.

Gacita Anthony M AM Fullenkamp Dominic E DE Ohiri Joyce J Pottinger Tess T Puckelwartz Megan J MJ Nobrega Marcelo A MA McNally Elizabeth M EM

Circulation 20210122 13

<h4>Background</h4>Inherited cardiomyopathy associates with a range of phenotypes, mediated by genetic and nongenetic factors. Noninherited cardiomyopathy also displays varying progression and outcomes. Expression of cardiomyopathy genes is under the regulatory control of promoters and enhancers, and human genetic variation in promoters and enhancers may contribute to this variability.<h4>Methods</h4>We superimposed epigenomic profiling from hearts and cardiomyocytes, including promoter-capture ...[more]

PMID: 33478249

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Project description:DNA sequence variation causes changes in gene expression, which in turn has profound effects on cellular states. These variations affect tissue development and may ultimately lead to pathological phenotypes. A genetic locus containing a sequence variation that affects gene expression is called an "expression quantitative trait locus" (eQTL). Whereas the impact of cellular context on expression levels in general is well established, a lot less is known about the cell-state specificity of eQTL. Previous studies differed with respect to how "dynamic eQTL" were defined. Here, we propose a unified framework distinguishing static, conditional and dynamic eQTL and suggest strategies for mapping these eQTL classes. Further, we introduce a new approach to simultaneously infer eQTL from different cell types. By using murine mRNA expression data from four stages of hematopoiesis and 14 related cellular traits, we demonstrate that static, conditional and dynamic eQTL, although derived from the same expression data, represent functionally distinct types of eQTL. While static eQTL affect generic cellular processes, non-static eQTL are more often involved in hematopoiesis and immune response. Our analysis revealed substantial effects of individual genetic variation on cell type-specific expression regulation. Among a total number of 3,941 eQTL we detected 2,729 static eQTL, 1,187 eQTL were conditionally active in one or several cell types, and 70 eQTL affected expression changes during cell type transitions. We also found evidence for feedback control mechanisms reverting the effect of an eQTL specifically in certain cell types. Loci correlated with hematological traits were enriched for conditional eQTL, thus, demonstrating the importance of conditional eQTL for understanding molecular mechanisms underlying physiological trait variation. The classification proposed here has the potential to streamline and unify future analysis of conditional and dynamic eQTL as well as many other kinds of QTL data.

Dataset Information

Genetic Variation in Enhancers Modifies Cardiomyopathy Gene Expression and Progression.

Background

Methods

Results

Conclusions

Publications

Genetic Variation in Enhancers Modifies Cardiomyopathy Gene Expression and Progression.

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