Dataset Information

High throughput in vivo functional validation of candidate congenital heart disease genes in Drosophila.

ABSTRACT: Genomic sequencing has implicated large numbers of genes and de novo mutations as potential disease risk factors. A high throughput in vivo model system is needed to validate gene associations with pathology. We developed a Drosophila-based functional system to screen candidate disease genes identified from Congenital Heart Disease (CHD) patients. 134 genes were tested in the Drosophila heart using RNAi-based gene silencing. Quantitative analyses of multiple cardiac phenotypes demonstrated essential structural, functional, and developmental roles for more than 70 genes, including a subgroup encoding histone H3K4 modifying proteins. We also demonstrated the use of Drosophila to evaluate cardiac phenotypes resulting from specific, patient-derived alleles of candidate disease genes. We describe the first high throughput in vivo validation system to screen candidate disease genes identified from patients. This approach has the potential to facilitate development of precision medicine approaches for CHD and other diseases associated with genetic factors.

SUBMITTER: Zhu JY

PROVIDER: S-EPMC5300701 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Publications

High throughput in vivo functional validation of candidate congenital heart disease genes in Drosophila.

Zhu Jun-Yi JY Fu Yulong Y Nettleton Margaret M Richman Adam A Han Zhe Z

eLife 20170120

Genomic sequencing has implicated large numbers of genes and de novo mutations as potential disease risk factors. A high throughput in vivo model system is needed to validate gene associations with pathology. We developed a Drosophila-based functional system to screen candidate disease genes identified from Congenital Heart Disease (CHD) patients. 134 genes were tested in the Drosophila heart using RNAi-based gene silencing. Quantitative analyses of multiple cardiac phenotypes demo ...[more]

PMID: 28084990

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Project description:Defects of atrial and ventricular septation are the most frequent form of congenital heart disease, accounting for almost 50% of all cases. We previously reported that a heterozygous G296S missense mutation of GATA4 caused atrial and ventricular septal defects and pulmonary valve stenosis in humans. GATA4 encodes a cardiac transcription factor, and when deleted in mice it results in cardiac bifida and lethality by embryonic day (E)9.5. In vitro, the mutant GATA4 protein has a reduced DNA binding affinity and transcriptional activity and abolishes a physical interaction with TBX5, a transcription factor critical for normal heart formation. To characterize the mutation in vivo, we generated mice harboring the same mutation, Gata4 G295S. Mice homozygous for the Gata4 G295S mutant allele have normal ventral body patterning and heart looping, but have a thin ventricular myocardium, single ventricular chamber, and lethality by E11.5. While heterozygous Gata4 G295S mutant mice are viable, a subset of these mice have semilunar valve stenosis and small defects of the atrial septum. Gene expression studies of homozygous mutant mice suggest the G295S protein can sufficiently activate downstream targets of Gata4 in the endoderm but not in the developing heart. Cardiomyocyte proliferation deficits and decreased cardiac expression of CCND2, a member of the cyclin family and a direct target of Gata4, were found in embryos both homozygous and heterozygous for the Gata4 G295S allele. To further define functions of the Gata4 G295S mutation in vivo, compound mutant mice were generated in which specific cell lineages harbored both the Gata4 G295S mutant and Gata4 null alleles. Examination of these mice demonstrated that the Gata4 G295S protein has functional deficits in early myocardial development. In summary, the Gata4 G295S mutation functions as a hypomorph in vivo and leads to defects in cardiomyocyte proliferation during embryogenesis, which may contribute to the development of congenital heart defects in humans.

Project description:BACKGROUND:Biological data that are well-organized by an ontology, such as Gene Ontology, enables high-throughput availability of the semantic web. It can also be used to facilitate high throughput classification of biomedical information. However, to our knowledge, no evaluation has been published on automating classifications of human diseases genes using Gene Ontology. In this study, we evaluate automated classifications of well-defined human disease genes using their Gene Ontology annotations and compared them to a gold standard. This gold standard was independently conceived by Valle's research group, and contains 923 human disease genes organized in 14 categories of protein function. RESULTS:Two automated methods were applied to investigate the classification of human disease genes into independently pre-defined categories of protein function. One method used the structure of Gene Ontology by pre-selecting 74 Gene Ontology terms assigned to 11 protein function categories. The second method was based on the similarity of human disease genes clustered according to the information-theoretic distance of their Gene Ontology annotations. Compared to the categorization of human disease genes found in the gold standard, our automated methods can achieve an overall 56% and 47% precision with 62% and 71% recall respectively. However, approximately 15% of the studied human disease genes remain without GO annotations. CONCLUSION:Automated methods can recapitulate a significant portion of classification of the human disease genes. The method using information-theoretic distance performs slightly better on the precision with some loss in recall. For some protein function categories, such as 'hormone' and 'transcription factor', the automated methods perform particularly well, achieving precision and recall levels above 75%. In summary, this study demonstrates that for semantic webs, methods to automatically classify or analyze a majority of human disease genes require significant progress in both the Gene Ontology annotations and particularly in the utilization of these annotations.

Dataset Information

High throughput in vivo functional validation of candidate congenital heart disease genes in Drosophila.

Publications

High throughput in vivo functional validation of candidate congenital heart disease genes in <i>Drosophila</i>.

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