Cardiac-specific developmental and epigenetic functions of Jarid2 during embryonic development.

Epigenetic regulation is critical in normal cardiac development. We have demonstrated that the deletion of Jarid2 (Jumonji (Jmj) A/T-rich interaction domain 2) in mice results in cardiac malformations recapitulating human congenital cardiac disease and dysregulation of gene expression. However, the precise developmental and epigenetic functions of Jarid2 within the developing heart remain to be elucidated. Here, we determined the cardiac-specific functions of Jarid2 and the genetic networks regulated by Jarid2. Jarid2 was deleted using different cardiac-specific Cre mice. The deletion of Jarid2 by Nkx2.5-Cre mice (Jarid2Nkx) caused cardiac malformations including ventricular septal defects, thin myocardium, hypertrabeculation, and neonatal lethality. Jarid2Nkx mice exhibited elevated expression of neural genes, cardiac jelly, and other key factors including Isl1 and Bmp10 in the developing heart. By employing combinatorial genome-wide approaches and molecular analyses, we showed that Jarid2 in the myocardium regulates a subset of Jarid2 target gene expression and H3K27me3 enrichment during heart development. Specifically, Jarid2 was required for PRC2 occupancy and H3K27me3 at the Isl1 promoter locus, leading to the proper repression of Isl1 expression. In contrast, Jarid2 deletion in differentiated cardiomyocytes by cTnt-Cre mice caused no gross morphological defects or neonatal lethality. Thus, the early deletion of Jarid2 in cardiac progenitors, prior to the differentiation of cardiac progenitors into cardiomyocytes, results in morphogenetic defects manifested later in development. Our studies reveal that there is a critical window during early cardiac progenitor differentiation when Jarid2 is crucial to establish the epigenetic landscape at later stages of development.

A library of yeast transcription factor motifs reveals a widespread function for Rsc3 in targeting nucleosome exclusion at promoters.

The sequence specificity of DNA-binding proteins is the primary mechanism by which the cell recognizes genomic features. Here, we describe systematic determination of yeast transcription factor DNA-binding specificities. We obtained binding specificities for 112 DNA-binding proteins representing 19 distinct structural classes. One-third of the binding specificities have not been previously reported. Several binding sequences have striking genomic distributions relative to transcription start sites, supporting their biological relevance and suggesting a role in promoter architecture. Among these are Rsc3 binding sequences, containing the core CGCG, which are found preferentially approximately 100 bp upstream of transcription start sites. Mutation of RSC3 results in a dramatic increase in nucleosome occupancy in hundreds of proximal promoters containing a Rsc3 binding element, but has little impact on promoters lacking Rsc3 binding sequences, indicating that Rsc3 plays a broad role in targeting nucleosome exclusion at yeast promoters.

Lrrc10 is a novel cardiac-specific target gene of Nkx2-5 and GATA4.

Cardiac gene expression is precisely regulated and its perturbation causes developmental defects and heart disease. Leucine-rich repeat containing 10 (Lrrc10) is a cardiac-specific factor that is crucial for proper cardiac development and deletion of Lrrc10 in mice results in dilated cardiomyopathy. However, the mechanisms regulating Lrrc10 expression in cardiomyocytes remain unknown. Therefore, we set out to determine trans-acting factors and cis-elements critical for mediating Lrrc10 expression. We identify Lrrc10 as a transcriptional target of Nkx2-5 and GATA4. The Lrrc10 promoter region contains two highly conserved cardiac regulatory elements, which are functional in cardiomyocytes but not in fibroblasts. In vivo, Nkx2-5 and GATA4 endogenously occupy the proximal and distal cardiac regulatory elements of Lrrc10 in the heart. Moreover, embryonic hearts of Nkx2-5 knockout mice have dramatically reduced expression of Lrrc10. These data demonstrate the importance of Nkx2-5 and GATA4 in regulation of Lrrc10 expression in vivo. The proximal cardiac regulatory element located at around -200bp is synergistically activated by Nkx2-5 and GATA4 while the distal cardiac regulatory element present around -3kb requires SRF in addition to Nkx2-5 and GATA4 for synergistic activation. Mutational analyses identify a pair of adjacent Nkx2-5 and GATA binding sites within the proximal cardiac regulatory element that are necessary to induce expression of Lrrc10. In contrast, only the GATA site is functional in the distal regulatory element. Taken together, our data demonstrate that the transcription factors Nkx2-5 and GATA4 cooperatively regulate cardiac-specific expression of Lrrc10.

Jarid2 (Jumonji, AT rich interactive domain 2) regulates NOTCH1 expression via histone modification in the developing heart.

Jarid2/Jumonji, the founding member of the Jmj factor family, critically regulates various developmental processes, including cardiovascular development. The Jmj family was identified as histone demethylases, indicating epigenetic regulation by Jmj proteins. Deletion of Jarid2 in mice resulted in cardiac malformation and increased endocardial Notch1 expression during development. Although Jarid2 has been shown to occupy the Notch1 locus in the developing heart, the precise molecular role of Jarid2 remains unknown. Here we show that deletion of Jarid2 results in reduced methylation of lysine 9 on histone H3 (H3K9) at the Notch1 genomic locus in embryonic hearts. Interestingly, SETDB1, a histone H3K9 methyltransferase, was identified as a putative cofactor of Jarid2 by yeast two-hybrid screening, and the physical interaction between Jarid2 and SETDB1 was confirmed by coimmunoprecipitation experiments. Concurrently, accumulation of SETDB1 at the site of Jarid2 occupancy was significantly reduced in Jarid2 knock out (KO) hearts. Employing genome-wide approaches, putative Jarid2 target genes regulated by SETDB1 via H3K9 methylation were identified in the developing heart by ChIP-chip. These targets are involved in biological processes that, when dysregulated, could manifest in the phenotypic defects observed in Jarid2 KO mice. Our data demonstrate that Jarid2 functions as a transcriptional repressor of target genes, including Notch1, through a novel process involving the modification of H3K9 methylation via specific interaction with SETDB1 during heart development. Therefore, our study provides new mechanistic insights into epigenetic regulation by Jarid2, which will enhance our understanding of the molecular basis of other organ development and biological processes.

Specificity landscapes of DNA binding molecules elucidate biological function.

Evaluating the specificity spectra of DNA binding molecules is a nontrivial challenge that hinders the ability to decipher gene regulatory networks or engineer molecules that act on genomes. Here we compare the DNA sequence specificities for different classes of proteins and engineered DNA binding molecules across the entire sequence space. These high-content data are visualized and interpreted using an interactive "specificity landscape" which simultaneously displays the affinity and specificity of a million-plus DNA sequences. Contrary to expectation, specificity landscapes reveal that synthetic DNA ligands match, and often surpass, the specificities of eukaryotic DNA binding proteins. The landscapes also identify differential specificity constraints imposed by diverse structural folds of natural and synthetic DNA binders. Importantly, the sequence context of a binding site significantly influences binding energetics, and utilizing the full contextual information permits greater accuracy in annotating regulatory elements within a given genome. Assigning such context-dependent binding values to every DNA sequence across the genome yields predictive genome-wide binding landscapes (genomescapes). A genomescape of a synthetic DNA binding molecule provided insight into its differential regulatory activity in cultured cells. The approach we describe will accelerate the creation of precision-tailored DNA therapeutics and uncover principles that govern sequence-specificity of DNA binding molecules.

Nucleating the assembly of macromolecular complexes.

Nature constructs intricate complexes containing numerous binding partners in order to direct a variety of cellular processes. Researchers have taken a cue from these events to develop synthetic molecules that can nucleate natural and unnatural interactions for a diverse set of applications. These molecules can be designed to drive protein dimerization or to modulate the interactions between proteins, lipids, DNA, or RNA and thereby alter cellular pathways. A variety of components within the cellular machinery can be recruited with or replaced by synthetic compounds. Directing the formation of multicomponent complexes with new synthetic molecules can allow unprecedented control over the cellular machinery.

CSI-Tree: a regression tree approach for modeling binding properties of DNA-binding molecules based on cognate site identification (CSI) data.

The identification and characterization of binding sites of DNA-binding molecules, including transcription factors (TFs), is a critical problem at the interface of chemistry, biology and molecular medicine. The Cognate Site Identification (CSI) array is a high-throughput microarray platform for measuring comprehensive recognition profiles of DNA-binding molecules. This technique produces datasets that are useful not only for identifying binding sites of previously uncharacterized TFs but also for elucidating dependencies, both local and nonlocal, between the nucleotides at different positions of the recognition sites. We have developed a regression tree technique, CSI-Tree, for exploring the spectrum of binding sites of DNA-binding molecules. Our approach constructs regression trees utilizing the CSI data of unaligned sequences. The resulting model partitions the binding spectrum into homogeneous regions of position specific nucleotide effects. Each homogeneous partition is then summarized by a position weight matrix (PWM). Hence, the final outcome is a binding intensity rank-ordered collection of PWMs each of which spans a different region in the binding spectrum. Nodes of the regression tree depict the critical position/nucleotide combinations. We analyze the CSI data of the eukaryotic TF Nkx-2.5 and two engineered small molecule DNA ligands and obtain unique insights into their binding properties. The CSI tree for Nkx-2.5 reveals an interaction between two positions of the binding profile and elucidates how different nucleotide combinations at these two positions lead to different binding affinities. The CSI trees for the engineered DNA ligands exhibit a common preference for the dinucleotide AA in the first two positions, which is consistent with preference for a narrow and relatively flat minor groove. We carry out a reanalysis of these data with a mixture of PWMs approach. This approach is an advancement over the simple PWM model and accommodates position dependencies based on only sequence data. Our analysis indicates that the dependencies revealed by the CSI-Tree are challenging to discover without the actual binding intensities. Moreover, such a mixture model is highly sensitive to the number and length of the sequences analyzed. In contrast, CSI-Tree provides interpretable and concise summaries of the complete recognition profiles of DNA-binding molecules by utilizing binding affinities.