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Deciphering the genetic architecture of human cardiac disorders is of fundamental importance but their underlying complexity is a major hurdle. We investigated the natural variation of cardiac performance in the sequenced inbred lines of the Drosophila Genetic Reference Panel (DGRP). Genome-wide associations studies (GWAS) identified genetic networks associated with natural variation of cardiac traits which were used to gain insights as to the molecular and cellular processes affected. Non-coding variants that we identified were used to map potential regulatory non-coding regions, which in turn were employed to predict transcription factors (TFs) binding sites. Cognate TFs, many of which themselves bear polymorphisms associated with variations of cardiac performance, were also validated by heart-specific knockdown. Additionally, we showed that the natural variations associated with variability in cardiac performance affect a set of genes overlapping those associated with average traits but through different variants in the same genes. Furthermore, we showed that phenotypic variability was also associated with natural variation of gene regulatory networks. More importantly, we documented correlations between genes associated with cardiac phenotypes in both flies and humans, which supports a conserved genetic architecture regulating adult cardiac function from arthropods to mammals. Specifically, roles for PAX9 and EGR2 in the regulation of the cardiac rhythm were established in both models, illustrating that the characteristics of natural variations in cardiac function identified in Drosophila can accelerate discovery in humans.

In mammals, both sterile wounding and infection induce inflammation and activate the innate immune system, and the combination of both challenges may lead to severe health defects, revealing the importance of the balance between the intensity and resolution of the inflammatory response for the organism’s fitness. Underlying mechanisms remain however elusive. Using Drosophila, we show that, upon infection with the entomopathogenic bacterium Pseudomonas entomophila (Pe) , a sterile wounding induces a reduced resistance and increased host mortality. To identify the molecular mechanisms underlying the susceptibility of wounded flies to bacterial infection, we analyzed the very first steps of the process by comparing the transcriptome landscape of infected (simple hit flies, SH), wounded and infected (double hit flies, DH) and wounded (control) flies. We observed that overexpressed genes in DH flies compared to SH ones are significantly enriched in genes related to stress, including members of the JNK pathway. We demonstrated that the JNK pathway plays a central role in the DH phenotype by manipulating the Jra/dJun activity. Moreover, the CrebA/Creb3-like transcription factor (TF) and its targets were up-regulated in SH flies and we show that CrebA is required for mounting an appropriate immune response. Drosophila thus appears as a relevant model to investigate interactions between trauma and infection and allows to unravel key pathways involved.

Deciphering the genetic architecture of human cardiac disorders is of fundamental importance but their underlying complexity is a major hurdle. We investigated the natural variation of cardiac performance in the sequenced inbred lines of the Drosophila Genetic Reference Panel (DGRP). Genome-wide associations studies (GWAS) identified genetic networks associated with natural variation of cardiac traits which were used to gain insights as to the molecular and cellular processes affected. Non-coding variants that we identified were used to map potential regulatory non-coding regions, which in turn were employed to predict transcription factors (TFs) binding sites. Cognate TFs, many of which themselves bear polymorphisms associated with variations of cardiac performance, were also validated by heart-specific knockdown. Additionally, we showed that the natural variations associated with variability in cardiac performance affect a set of genes overlapping those associated with average traits but through different variants in the same genes. Furthermore, we showed that phenotypic variability was also associated with natural variation of gene regulatory networks. More importantly, we documented correlations between genes associated with cardiac phenotypes in both flies and humans, which supports a conserved genetic architecture regulating adult cardiac function from arthropods to mammals. Specifically, roles for PAX9 and EGR2 in the regulation of the cardiac rhythm were established in both models, illustrating that the characteristics of natural variations in cardiac function identified in Drosophila can accelerate discovery in humans.

Understanding the relationship between genetic variations and variations in complex and quantitative phenotypes remains an ongoing challenge. While genome-wide association studies (GWAS) have become a vital tool for identifying single-locus associations, we lack methods for identifying epistatic interactions. In this article, we propose a novel method for high-order epistasis detection using mixed effect conditional inference forest (epiMEIF). The epiMEIF model is fitted on a group of potential causal SNPs and the tree structure in the forest facilitates the identification of n-way interactions between the SNPs. Additional testing strategies further improve the robustness of the method. We demonstrate its ability to detect true n-way interactions via extensive simulations in both cross-sectional and longitudinal synthetic datasets. This is further illustrated in an application to reveal epistatic interactions from natural variations of cardiac traits in flies (Drosophila). Overall, the method provides a generalized way to identify high order interactions from any GWAS data, thereby greatly improving the detection of the genetic architecture of complex phenotypes. Competing Interest Statement The authors have declared no competing interest.

Deciphering the genetic architecture of human cardiac disorders is of fundamental importance but their underlying complexity is a major hurdle. We investigated the natural variation of cardiac performance in the sequenced inbred lines of the Drosophila Genetic Reference Panel (DGRP). Genome Wide Associations Studies (GWAS) identified genetic networks associated with natural variation of cardiac traits which were used to gain insights as to the molecular and cellular processes affected. Non-coding variants that we identified were used to map potential regulatory non-coding regions, which in turn were employed to predict Transcription Factors (TFs) binding sites. Cognate TFs, many of which themselves bear polymorphisms associated with variations of cardiac performance, were also validated by heart specific knockdown. Additionally, we showed that the natural variations associated with variability in cardiac performance affect a set of genes overlapping those associated with average traits but through different variants in the same genes. Furthermore, we showed that phenotypic variability was also associated with natural variation of gene regulatory networks. More importantly, we documented correlations between genes associated with cardiac phenotypes in both flies and humans, which supports a conserved genetic architecture regulating adult cardiac function from arthropods to mammals. Specifically, roles for PAX9 and EGR2 in the regulation of the cardiac rhythm were established in both models, illustrating that the characteristics of natural variations in cardiac function identified in Drosophila can accelerate discovery in humans.

Cardiopathies are one of the leading causes of death in obese diabetics. Resulting in part from junk food, diabetic cardiomyopathies are notably characterized by contractile dysfunctions. Using the Drosophila model for cardiac function in pathophysiological context, we identified a set of candidate genes, expressed by the heart, whose expression is modulated by acute challenge on High Sugar and High Fat regimes. Genes encoding core components of key homeostatic pathways and proteins such as 1C-metabolism homeostasis, the Galactose metabolism pathway and metabolites transporters, were identified and characterized as adaptative factors of cardiac function under nutritional stresses. In addition, putative secreted proteins were found dysregulated, highlighting the heart as a secretory organ in hyperglycemia and hyperlipidemia. In particular, we characterized the Fit satiety hormone as a new fly cardiokine, which autonomously modulates the cardiac function and remotely affects feeding behavior. Overall, our study uncovered new roles for metabolic pathways and cardiokines, and highlights autonomous and systemic adjustable responses of the heart to nutritional stresses.Competing Interest StatementThe authors have declared no competing interest.Footnotes* Cardiopathies are one of the leading causes of death in obese diabetics. Resulting in part from junk food, diabetic cardiomyopathies are notably characterized by contractile dysfunctions. Using the Drosophila model for cardiac function in pathophysiological context, we identified a set of candidate genes, expressed by the heart, whose expression is modulated by acute challenge on High Sugar and High Fat regimes. Genes encoding core components of key homeostatic pathways and proteins such as 1C-metabolism homeostasis, the Galactose metabolism pathway and metabolites transporters, were identified and characterized as adaptative factors of cardiac function under nutritional stresses. In addition, putative secreted proteins were found dysregulated, highlighting the heart as a secretory organ in hyperglycemia and hyperlipidemia. In particular, we characterized the Fit satiety hormone as a new fly cardiokine, which autonomously modulates the cardiac function and remotely affects feeding behavior. Overall, our study uncovered new roles for metabolic pathways and cardiokines, and highlights autonomous and systemic adjustable responses of the heart to nutritional stresses.

Deciphering the genetic architecture of human cardiac disorders is of fundamental importance but their underlying complexity is a major hurdle. We investigated the natural variation of cardiac performance in the sequenced inbred lines of the Drosophila Genetic Reference Panel (DGRP). Genome Wide Associations Studies (GWAS) identified genetic networks associated with natural variation of cardiac traits which were used to gain insights as to the molecular and cellular processes affected. Non-coding variants that we identified were used to map potential regulatory non-coding regions, which in turn were employed to predict Transcription Factors (TFs) binding sites. Cognate TFs, many of which themselves bear polymorphisms associated with variations of cardiac performance, were also validated by heart specific knockdown. Additionally, we showed that the natural variations associated with variability in cardiac performance affect a set of genes overlapping those associated with average traits but through different variants in the same genes. Furthermore, we showed that phenotypic variability was also associated with natural variation of gene regulatory networks. More importantly, we documented correlations between genes associated with cardiac phenotypes in both flies and humans, which supports a conserved genetic architecture regulating adult cardiac function from arthropods to mammals. Specifically, roles for PAX9 and EGR2 in the regulation of the cardiac rhythm were established in both models, illustrating that the characteristics of natural variations in cardiac function identified in Drosophila can accelerate discovery in humans. Competing Interest Statement The authors have declared no competing interest.

The identification of genetic factors influencing cardiac senescence in natural populations is central to our understanding of cardiac aging and to identify the etiology of associated cardiac disorders in human populations. However, the genetic underpinning of complex traits in human is almost impossible, due to the infeasibility to control genetic background and gene-environment interactions. Drosophila has striking similarities in cardiac aging with humans, highlighting the conserved nature of cardiac aging for organisms with a heart. Leveraging on a large collection of inbred lines from the Drosophila Genetic Reference Panel (DGRP), we provide an accurate analysis of cardiac senescence in a natural population of flies. This permitted the discovery of an unprecedented number of variants and associated genes significantly associated to the natural variation of cardiac aging. We focused on the function of the PAR domain bZIP transcription factor Pdp1 for which several variants were found associated with natural variation of the aging of multiple cardiac functional traits. We demonstrated that Pdp1 cell autonomously plays a central role in cardiac senescence and might do so by regulating mitochondria homeostasis. Overall, our work provides a unique resource regarding the genetics of cardiac aging in a natural population.

Rosalind Eeles, Christopher Haiman and colleagues report genome-wide association and meta-analyses of prostate cancer in populations of European, African, Japanese and Latino ancestry. They identify 23 new susceptibility loci, including one associated with early-onset prostate cancer. Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of >10 million SNPs in 43,303 prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three new susceptibility loci were identified at association P < 5 × 10 −8 ; 15 variants were identified among men of European ancestry, 7 were identified in multi-ancestry analyses and 1 was associated with early-onset prostate cancer. These 23 variants, in combination with known prostate cancer risk variants, explain 33% of the familial risk for this disease in European-ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the usefulness of combining ancestrally diverse populations to discover risk loci for disease.