Genes and networks regulating cardiac development and function in flies: genetic and functional genomic approaches
Author(s) -
Denis Seyres,
Laurence Röder,
Laurent Perrin
Publication year - 2012
Publication title -
briefings in functional genomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.22
H-Index - 67
eISSN - 2041-2647
pISSN - 2041-2649
DOI - 10.1093/bfgp/els028
Subject(s) - biology , functional genomics , computational biology , gene regulatory network , rna interference , function (biology) , genomics , gene , heart development , forward genetics , genetic screen , transcription factor , genetics , genome , phenotype , gene expression , rna , embryonic stem cell
The Drosophila heart has emerged as a powerful model system for cardiovascular research. This simple organ, composed of only 104 cardiomyocytes and associated pericardiac cells, has been the focus of numerous candidate gene approaches in the last 2 decades, which have unraveled a number of transcription factors and signaling pathways involved in the regulation of early cardiac development. Importantly, these regulators seem to have largely conserved functions in mammals. Recent studies also demonstrated the usefulness of the fly circulatory system to investigate molecular mechanisms involved in the control of the establishment and maintenance of the cardiac function. In this review, we have focused on how new technological and conceptual advances in the field of functional genomics have impacted research on the cardiovascular system in Drosophila. Genome-scale genetic screens were conducted taking advantage of recently developed ribonucleic acid interference transgenic lines and molecularly defined genetic deficiencies, which have provided new insights into the genetics of both the developmental control of heart formation and cardiac function. In addition, a comprehensive picture of the transcriptional network controlling heart formation is emerging, thanks to newly developed genomic approaches which allow global and unbiased identification of the underlying components of gene regulatory circuits.
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