Abstract
Background: Rapid advance of genome technologies accelerate the discovery of genetic basis of cardiomyopathy and heart failure and also enable system biology studies to pinpoint underlying mechanism. However, the limited throughput of mammalian models restricted the number of genes that can be studied in a particular lab. Adult zebrafish has been recently pursued as a new model with higher throughput. However, as a non-mammalian model, its conservation is not tested. Objective: To assess the conservation of zebrafish for genetic studies of human dilated cardiomyopathy (DCM) via transcriptome analysis of 51 known DCM-causative genes. Methods and Results: By conducting RNA-sequencing (RNA-seq) analysis of larva and adult zebrafish, we identified genes with high expression level in the heart and fetal gene program using differential expression between embryonic and adult stages. We then searched zebrafish orthologues for 51 reported human DCM-causative or associated genes and identified zebrafish orthologues for 49 of them. While 30 genes have a single orthologue, 14 genes have two homologues and the remaining 5 genes have more than three. We then applied the transcriptome data to prioritize these homologues for the 19 DCM causative genes with more than one homologue. Based on the cardiac abundance and cardiac enrichment hypothesis, we are able to recommend a single zebrafish homologue of high priority for 12 out of 19 DCM genes, 2 zebrafish homologues of high priority for ACTC1. Interestingly, our expressional data suggested zebrafish othologues for human MYH6 and MYH7 , respectively. Similar to that in mammals, these two zebrafish othologues are oppositely expressed during zebrafish embryonic and adult stage. Conclusions: Orthologues for the majority of DCM causative genes can be found in Zebrafish, supporting its usage as a conserved vertebrate model for studying DCM. The definition of cardiac transcriptome in zebrafish will facilitate the future system biology studies. This vertebrate model with higher throughput can be further leveraged to validate the novel variants identified from human patients, to understand underlying signaling pathways and to develop novel therapeutics.
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