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Inferring dynamic gene regulatory networks in cardiac differentiation through the integration of multi-dimensional data.

Gong W, Koyano-Nakagawa N, Li T, Garry DJ - BMC Bioinformatics (2015)

Bottom Line: Our method not only infers the time-varying networks between different stages of heart development, but it also identifies the TF binding sites associated with promoter or enhancers of downstream genes.Our model also predicted the key regulatory networks for the ESC-MES, MES-CP and CP-CM transitions.This method will allow one to rapidly determine the cis-modules that regulate key genes during cardiac differentiation.

View Article: PubMed Central - PubMed

Affiliation: Lillehei Heart Institute, University of Minnesota, 2231 6th St S.E, 4-165 CCRB, Minneapolis, MN, 55114, USA. gongx030@umn.edu.

ABSTRACT

Background: Decoding the temporal control of gene expression patterns is key to the understanding of the complex mechanisms that govern developmental decisions during heart development. High-throughput methods have been employed to systematically study the dynamic and coordinated nature of cardiac differentiation at the global level with multiple dimensions. Therefore, there is a pressing need to develop a systems approach to integrate these data from individual studies and infer the dynamic regulatory networks in an unbiased fashion.

Results: We developed a two-step strategy to integrate data from (1) temporal RNA-seq, (2) temporal histone modification ChIP-seq, (3) transcription factor (TF) ChIP-seq and (4) gene perturbation experiments to reconstruct the dynamic network during heart development. First, we trained a logistic regression model to predict the probability (LR score) of any base being bound by 543 TFs with known positional weight matrices. Second, four dimensions of data were combined using a time-varying dynamic Bayesian network model to infer the dynamic networks at four developmental stages in the mouse [mouse embryonic stem cells (ESCs), mesoderm (MES), cardiac progenitors (CP) and cardiomyocytes (CM)]. Our method not only infers the time-varying networks between different stages of heart development, but it also identifies the TF binding sites associated with promoter or enhancers of downstream genes. The LR scores of experimentally verified ESCs and heart enhancers were significantly higher than random regions (p <10(-100)), suggesting that a high LR score is a reliable indicator for functional TF binding sites. Our network inference model identified a region with an elevated LR score approximately -9400 bp upstream of the transcriptional start site of Nkx2-5, which overlapped with a previously reported enhancer region (-9435 to -8922 bp). TFs such as Tead1, Gata4, Msx2, and Tgif1 were predicted to bind to this region and participate in the regulation of Nkx2-5 gene expression. Our model also predicted the key regulatory networks for the ESC-MES, MES-CP and CP-CM transitions.

Conclusion: We report a novel method to systematically integrate multi-dimensional -omics data and reconstruct the gene regulatory networks. This method will allow one to rapidly determine the cis-modules that regulate key genes during cardiac differentiation.

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Related in: MedlinePlus

Predicted transcription factor binding sites around the 40-kb cis-region of theNkx2-5gene. The cardiac regulatory region (−9435/-8922) has been reported by Lien et al. Brown bars indicate the presence of links and associated transcription factors at distinct stage transitions.
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Fig3: Predicted transcription factor binding sites around the 40-kb cis-region of theNkx2-5gene. The cardiac regulatory region (−9435/-8922) has been reported by Lien et al. Brown bars indicate the presence of links and associated transcription factors at distinct stage transitions.

Mentions: Nkx2-5 is one of the essential transcription factors mediating heart development. Without Nkx2-5 function, the heart primordium does not loop properly and embryos die at embryonic day (E) 9.5 [53,54]. It has been reported that a region −9435 bp to −8922 bp upstream of Nkx2-5's TSS contains an enhancer that controls its early cardiac-specific transcription and this regulation is Gata-dependent [55,56]. Our network inference model predicted that this region contains a high LR score region and peaks approximately −9400 bp upstream of TSS (Figure 3). Around this peak LR score, there was a dip of H3K27ac that contains the clustered binding sites of the Hippo signaling pathway player Tead1, Gata4, BMP signaling pathway players, Msx2 and Tgif1. Tead1 binding motif is known to be enriched around sequences pulled down by p300, Gata4, Nkx2-5, and Mef2a using ChIP assays [2]. Msx1 and Msx2 functions have been implied in endothelial-mesenchymal transformation of the atrioventricular cushions and patterning of the atrioventricular myocardium. BMP signaling pathway is an important regulator of heart development [57]. Although it is still unknown whether these factors directly bind to the Nkx2-5 regulatory region, we predict that this regulatory module may be functionally important to activate Nkx2-5 in cardiac progenitors [58-60]. Additional file 1: Figure S6A-C are additional examples of Gata4, Gata6, and Bhlh40 genes demonstrating the overlap of predicted TFBS and experimentally detected enhancers. These individual examples demonstrate that our network inference model identified many biologically verified links and suggests that novel links may be of biological significance.Figure 3


Inferring dynamic gene regulatory networks in cardiac differentiation through the integration of multi-dimensional data.

Gong W, Koyano-Nakagawa N, Li T, Garry DJ - BMC Bioinformatics (2015)

Predicted transcription factor binding sites around the 40-kb cis-region of theNkx2-5gene. The cardiac regulatory region (−9435/-8922) has been reported by Lien et al. Brown bars indicate the presence of links and associated transcription factors at distinct stage transitions.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4359553&req=5

Fig3: Predicted transcription factor binding sites around the 40-kb cis-region of theNkx2-5gene. The cardiac regulatory region (−9435/-8922) has been reported by Lien et al. Brown bars indicate the presence of links and associated transcription factors at distinct stage transitions.
Mentions: Nkx2-5 is one of the essential transcription factors mediating heart development. Without Nkx2-5 function, the heart primordium does not loop properly and embryos die at embryonic day (E) 9.5 [53,54]. It has been reported that a region −9435 bp to −8922 bp upstream of Nkx2-5's TSS contains an enhancer that controls its early cardiac-specific transcription and this regulation is Gata-dependent [55,56]. Our network inference model predicted that this region contains a high LR score region and peaks approximately −9400 bp upstream of TSS (Figure 3). Around this peak LR score, there was a dip of H3K27ac that contains the clustered binding sites of the Hippo signaling pathway player Tead1, Gata4, BMP signaling pathway players, Msx2 and Tgif1. Tead1 binding motif is known to be enriched around sequences pulled down by p300, Gata4, Nkx2-5, and Mef2a using ChIP assays [2]. Msx1 and Msx2 functions have been implied in endothelial-mesenchymal transformation of the atrioventricular cushions and patterning of the atrioventricular myocardium. BMP signaling pathway is an important regulator of heart development [57]. Although it is still unknown whether these factors directly bind to the Nkx2-5 regulatory region, we predict that this regulatory module may be functionally important to activate Nkx2-5 in cardiac progenitors [58-60]. Additional file 1: Figure S6A-C are additional examples of Gata4, Gata6, and Bhlh40 genes demonstrating the overlap of predicted TFBS and experimentally detected enhancers. These individual examples demonstrate that our network inference model identified many biologically verified links and suggests that novel links may be of biological significance.Figure 3

Bottom Line: Our method not only infers the time-varying networks between different stages of heart development, but it also identifies the TF binding sites associated with promoter or enhancers of downstream genes.Our model also predicted the key regulatory networks for the ESC-MES, MES-CP and CP-CM transitions.This method will allow one to rapidly determine the cis-modules that regulate key genes during cardiac differentiation.

View Article: PubMed Central - PubMed

Affiliation: Lillehei Heart Institute, University of Minnesota, 2231 6th St S.E, 4-165 CCRB, Minneapolis, MN, 55114, USA. gongx030@umn.edu.

ABSTRACT

Background: Decoding the temporal control of gene expression patterns is key to the understanding of the complex mechanisms that govern developmental decisions during heart development. High-throughput methods have been employed to systematically study the dynamic and coordinated nature of cardiac differentiation at the global level with multiple dimensions. Therefore, there is a pressing need to develop a systems approach to integrate these data from individual studies and infer the dynamic regulatory networks in an unbiased fashion.

Results: We developed a two-step strategy to integrate data from (1) temporal RNA-seq, (2) temporal histone modification ChIP-seq, (3) transcription factor (TF) ChIP-seq and (4) gene perturbation experiments to reconstruct the dynamic network during heart development. First, we trained a logistic regression model to predict the probability (LR score) of any base being bound by 543 TFs with known positional weight matrices. Second, four dimensions of data were combined using a time-varying dynamic Bayesian network model to infer the dynamic networks at four developmental stages in the mouse [mouse embryonic stem cells (ESCs), mesoderm (MES), cardiac progenitors (CP) and cardiomyocytes (CM)]. Our method not only infers the time-varying networks between different stages of heart development, but it also identifies the TF binding sites associated with promoter or enhancers of downstream genes. The LR scores of experimentally verified ESCs and heart enhancers were significantly higher than random regions (p <10(-100)), suggesting that a high LR score is a reliable indicator for functional TF binding sites. Our network inference model identified a region with an elevated LR score approximately -9400 bp upstream of the transcriptional start site of Nkx2-5, which overlapped with a previously reported enhancer region (-9435 to -8922 bp). TFs such as Tead1, Gata4, Msx2, and Tgif1 were predicted to bind to this region and participate in the regulation of Nkx2-5 gene expression. Our model also predicted the key regulatory networks for the ESC-MES, MES-CP and CP-CM transitions.

Conclusion: We report a novel method to systematically integrate multi-dimensional -omics data and reconstruct the gene regulatory networks. This method will allow one to rapidly determine the cis-modules that regulate key genes during cardiac differentiation.

Show MeSH
Related in: MedlinePlus