An encyclopedia of mouse DNA elements (Mouse ENCODE)

Stamatoyannopoulos, J; Snyder, M; Hardison, Ross C.; Ren, Bing; Gingeras, T; Gilbert, David M.; Groudine, Mark; Bender, Michael A.; Kaul, Rajinder; Canfield, Theresa; Giste, Erica; Johnson, Audra; Zhang, Mia; Balasundaram, Gayathri; Byron, Rachel; Roach, Vaughan; Sabo, Peter J.; Sandstrom, Richard; Stehling, A Sandra; Thurman, Robert E.; Weissman, Sherman M.; Cayting, Philip; Hariharan, Manoj; Jin, Lian; Cheng, Yong; Landt, Stephen G.; Ma, Zhihai; Wold, B; Dekker, Job; Crawford, Gregory E.; Keller, Cheryl A.; Wu, Weisheng; Morrissey, Christopher A.; Kumar, Swathi Ashok; Mishra, Tejaswini; Jain, Deepti; Byrska-Bishop, Marta; Blankenberg, Daniel; Lajoie, Bryan R.; Jain, Gaurav; Sanyal, Amartya; Chen, Kaun-Bei; Denas, Olgert; Taylor, James; Blobel, Gerd A.; Weiss, Mitchell J.; Pimkin, Max; Deng, Wulan; Marinov, Georgi K.; Williams, Brian A.; Fisher-Aylor, Katherine I.; DeSalvo, Gilberto; Kiralusha, Anthony; Trout, Diane; Amrhein, Henry; Mortazavi, A; Edsall, Lee; McCleary, David; Kuan, Samantha; Shen, Yin; Yue, Feng; Ye, Zhen; Davis, Carrie A.; Zaleski, Chris; Jha, Sonali; Xue, Chenghai; Dobin, Alexander; Lin, Wei; Fastuca, Meagan; Wang, Huaien; Guigó, Roderic; Djebali, Sarah; Lagarde, Julien; Ryba, Tyrone; Sasaki, Takayo; Malladi, Venkat S.; Cline, Melissa; Kirkup, Vanessa M.; Learned, Katrina; Rosenbloom, Kate R.; Kent, W. James; Feingold, Elise A.; Good, Peter J.; Pazin, Michael J.; Lowdon, Rebecca F.; Adams, Leslie B.

doi:10.1186/gb-2012-13-8-418

Cited by 412 publications

(292 citation statements)

References 22 publications

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“…3B,D). These data correspond to the ENCODE data for H3K27ac and Pol2 in the heart (Stamatoyannopoulos et al, 2012) (Fig. 3C).…”

Section: Resultssupporting

confidence: 82%

“…However, the −40/−35 kb region relative to Nppa, described above as a potential enhancer, was highly acetylated already in the normal heart (our data; Papait et al, 2013;Stamatoyannopoulos et al, 2012), and is likely to be involved in the adult expression of Nppb, which, in contrast to Nppa, is still expressed in the ventricles after birth. After TAC, the levels of H3K27ac in this region were significantly lower than in the normal heart.…”

Section: Discussion the Nppa-nppb Cluster Is Confined To A Regulatorymentioning

confidence: 54%

“…We observed that the mouse Nppb promoter was required for basal Nppb expression in the fetal and adult heart, but not required (Stamatoyannopoulos et al, 2012) and overlapping with the predicted enhancers (van Duijvenboden et al, 2016). Red bars, developmental and stress-response regions of Nppb; green bars, developmental and stress-response regions of Nppa.…”

Section: Discussion the Nppa-nppb Cluster Is Confined To A Regulatorymentioning

confidence: 90%

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Identification of a regulatory domain controlling the Nppa-Nppb gene cluster during heart development and stress

et al. 2016

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The paralogous genes Nppa and Nppb are organized in an evolutionarily conserved cluster and provide a valuable model for studying co-regulation and regulatory landscape organization during heart development and disease. Here, we analyzed the chromatin conformation, epigenetic status and enhancer potential of sequences of the Nppa-Nppb cluster in vivo. Our data indicate that the regulatory landscape of the cluster is present within a 60-kb domain centered around Nppb. Both promoters and several potential regulatory elements interact with each other in a similar manner in different tissues and developmental stages. The distribution of H3K27ac and the association of Pol2 across the locus changed during cardiac hypertrophy, revealing their potential involvement in stress-mediated gene regulation. Functional analysis of double-reporter transgenic mice revealed that Nppa and Nppb share developmental, but not stressresponse, enhancers, responsible for their co-regulation. Moreover, the Nppb promoter was required, but not sufficient, for hypertrophy-induced Nppa expression. In summary, the developmental regulation and stress response of the Nppa-Nppb cluster involve the concerted action of multiple enhancers and epigenetic changes distributed across a structurally rigid regulatory domain.

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“…3B,D). These data correspond to the ENCODE data for H3K27ac and Pol2 in the heart (Stamatoyannopoulos et al, 2012) (Fig. 3C).…”

Section: Resultssupporting

confidence: 82%

Section: Discussion the Nppa-nppb Cluster Is Confined To A Regulatorymentioning

confidence: 54%

Section: Discussion the Nppa-nppb Cluster Is Confined To A Regulatorymentioning

confidence: 90%

See 1 more Smart Citation

Identification of a regulatory domain controlling the Nppa-Nppb gene cluster during heart development and stress

et al. 2016

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“…To train SVMs using ES chromatin state data, we first gathered 55 mouse ES ChIP-seq and DNaseI-seq experiments from a variety of sources [33][34][35][36][37][38][39][40][41][42]. We defined positive training sets from the top-most Cdx2 binding events for each condition-specific and condition-independent permutation (up to a maximum of 4,000 binding events), and we also defined a negative training set of 10,000 matches to the Cdx2 cognate binding motif (as defined by UniProbe [43]) that were not bound by Cdx2 in any experiment.…”

Section: Svm Analysismentioning

confidence: 99%

An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding

Mahony

Edwards

Mazzoni

et al. 2014

Lecture Notes in Computer Science

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Regulatory proteins can bind to different sets of genomic targets in various cell types or conditions. To reliably characterize such condition-specific regulatory binding we introduce MultiGPS, an integrated machine learning approach for the analysis of multiple related ChIP-seq experiments. MultiGPS is based on a generalized Expectation Maximization framework that shares information across multiple experiments for binding event discovery. We demonstrate that our framework enables the simultaneous modeling of sparse condition-specific binding changes, sequence dependence, and replicate-specific noise sources. MultiGPS encourages consistency in reported binding event locations across multiple-condition ChIP-seq datasets and provides accurate estimation of ChIP enrichment levels at each event. MultiGPS's multi-experiment modeling approach thus provides a reliable platform for detecting differential binding enrichment across experimental conditions. We demonstrate the advantages of MultiGPS with an analysis of Cdx2 binding in three distinct developmental contexts. By accurately characterizing condition-specific Cdx2 binding, MultiGPS enables novel insight into the mechanistic basis of Cdx2 site selectivity. Specifically, the condition-specific Cdx2 sites characterized by MultiGPS are highly associated with preexisting genomic context, suggesting that such sites are pre-determined by cell-specific regulatory architecture. However, MultiGPS-defined condition-independent sites are not predicted by pre-existing regulatory signals, suggesting that Cdx2 can bind to a subset of locations regardless of genomic environment. A summary of this paper appears in the proceedings Competing Interests: The authors have declared that no competing interests exist. * E-mail: mahony@psu.edu (SM); dkg@mit.edu (DKG) . These authors contributed equally to this work.

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“…The SNPs that segregated were scanned for regulatory features in the Ensembl.org regulatory feature build (release 73), containing the ENCODE data (Stamatoyannopoulos et al 2012). In addition, the entire region of the overlapping QTL interval containing the 32 SNPs was analyzed using the Transfac Professional Database (http://www.biobaseinternational.com) (Matys et al 2006).…”

Section: Regulatory Sequence Identificationmentioning

confidence: 99%

Identification of a QTL in Mus musculus for Alcohol Preference, Withdrawal, and Ap3m2 Expression Using Integrative Functional Genomics and Precision Genetics

et al. 2014

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Extensive genetic and genomic studies of the relationship between alcohol drinking preference and withdrawal severity have been performed using animal models. Data from multiple such publications and public data resources have been incorporated in the GeneWeaver database with .60,000 gene sets including 285 alcohol withdrawal and preference-related gene sets. Among these are evidence for positional candidates regulating these behaviors in overlapping quantitative trait loci (QTL) mapped in distinct mouse populations. Combinatorial integration of functional genomics experimental results revealed a single QTL positional candidate gene in one of the loci common to both preference and withdrawal. Functional validation studies in Ap3m2 knockout mice confirmed these relationships. Genetic validation involves confirming the existence of segregating polymorphisms that could account for the phenotypic effect. By exploiting recent advances in mouse genotyping, sequence, epigenetics, and phylogeny resources, we confirmed that Ap3m2 resides in an appropriately segregating genomic region. We have demonstrated genetic and alcohol-induced regulation of Ap3m2 expression. Although sequence analysis revealed no polymorphisms in the Ap3m2-coding region that could account for all phenotypic differences, there are several upstream SNPs that could. We have identified one of these to be an H3K4me3 site that exhibits strain differences in methylation. Thus, by making cross-species functional genomics readily computable we identified a common QTL candidate for two related bio-behavioral processes via functional evidence and demonstrate sufficiency of the genetic locus as a source of variation underlying two traits. FINDING the genetic and genomic basis for complex disorders has been a major challenge, particularly for behavioral traits. This is because the disorders are highly heterogeneous in their manifestation and regulation, requiring a match of numerous genes to many aspects of the disorders. A compelling approach to this problem lies in integration of numerous disparate data sets across species, each aimed at characterizing the mechanistic biological underpinnings for the behaviors underlying these disorders as modeled in various species. Alcoholism and alcohol use-related disorders are complex, heritable traits that have been the subject of extensive genomic and genetic investigations (Morozova et al. 2012). These traits are particularly challenging because of their heterogeneity and the presence of multiple overlapping subsystems that subserve them (Gould and Gottesman 2006;Crabbe 2012). Many rodent quantitative trait loci (QTL) have been mapped for alcohol-related traits (Ehlers et al. 2010), gene expression analyses have been performed in a variety of populations, and a long history of alcoholism genetics in humans has led to numerous genome-wide association studies (GWAS) or linkage studies (Enoch 2013). QTL mapping studies historically had very low resolution, and many have been performed using populations for which...

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An encyclopedia of mouse DNA elements (Mouse ENCODE)

Abstract: To complement the human Encyclopedia of DNA Elements (ENCODE) project and to enable a broad range of mouse genomics efforts, the Mouse ENCODE Consortium is applying the same experimental pipelines developed for human ENCODE to annotate the mouse genome.

Cited by 412 publications

References 22 publications

Identification of a regulatory domain controlling the Nppa-Nppb gene cluster during heart development and stress

Identification of a regulatory domain controlling the Nppa-Nppb gene cluster during heart development and stress

An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding

Identification of a QTL in Mus musculus for Alcohol Preference, Withdrawal, and Ap3m2 Expression Using Integrative Functional Genomics and Precision Genetics

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