We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor–binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs. We constructed hierarchical networks of transcription factor–binding and microRNA interactions and discovered chromosomal locations bound by an unusually large number of transcription factors. Different patterns of chromatin composition and histone modification were revealed between chromosome arms and centers, with similarly prominent differences between autosomes and the X chromosome. Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome.

Regulatory T (Treg) and T helper 17 (Th17) cells were recently proposed to be reciprocally regulated during differentiation. To understand the underlying mechanisms, we utilized a Th17 reporter mouse with a red fluorescent protein (RFP) sequence inserted into the interleukin-17F (IL-17F) gene. Using IL-17F-RFP together with a Foxp3 reporter, we found that the development of Th17 and Foxp3(+) Treg cells was associated in immune responses. Although TGF-beta receptor I signaling was required for both Foxp3 and IL-17 induction, SMAD4 was only involved in Foxp3 upregulation. Foxp3 inhibited Th17 differentiation by antagonizing the function of the transcription factors RORgammat and ROR*. In contrast, IL-6 overcame this suppressive effect of Foxp3 and, together with IL-1, induced genetic reprogramming in Foxp3(+) Treg cells. STAT3 regulated Foxp3 downregulation, whereas STAT3, RORgamma, and ROR* were required for IL-17 expression in Treg cells. Our data demonstrate molecular antagonism and plasticity of Treg and Th17 cell programs.

To gain insight into how genomic information is translated into cellular and developmental programs, the Drosophila model organism Encyclopedia of DNA Elements (modENCODE) project is comprehensively mapping transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines. We have generated more than 700 data sets and discovered protein-coding, noncoding, RNA regulatory, replication, and chromatin elements, more than tripling the annotated portion of the Drosophila genome. Correlated activity patterns of these elements reveal a functional regulatory network, which predicts putative new functions for genes, reveals stage- and tissue-specific regulators, and enables gene-expression prediction. Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation.

A high-quality human functional protein interaction network is constructed. Its utility is demonstrated in the identification of cancer candidate genes.

Insulators are DNA sequences that control the interactions among genomic regulatory elements and act as chromatin boundaries. A thorough understanding of their location and function is necessary to address the complexities of metazoan gene regulation. We studied by ChIP–chip the genome-wide binding sites of 6 insulator-associated proteins—dCTCF, CP190, BEAF-32, Su(Hw), Mod(mdg4), and GAF—to obtain the first comprehensive map of insulator elements in Drosophila embryos. We identify over 14,000 putative insulators, including all classically defined insulators. We find two major classes of insulators defined by dCTCF/CP190/BEAF-32 and Su(Hw), respectively. Distributional analyses of insulators revealed that particular sub-classes of insulator elements are excluded between cis-regulatory elements and their target promoters; divide differentially expressed, alternative, and divergent promoters; act as chromatin boundaries; are associated with chromosomal breakpoints among species; and are embedded within active chromatin domains. Together, these results provide a map demarcating the boundaries of gene regulatory units and a framework for understanding insulator function during the development and evolution of Drosophila.

TGFbeta signaling controls diverse normal developmental processes and pathogenesis of diseases including cancer and autoimmune and fibrotic diseases. TGFbeta responses are generally mediated through transcriptional functions of Smads. A key step in TGFbeta signaling is ligand-induced phosphorylation of receptor-activated Smads (R-Smads) catalyzed by the TGFbeta type I receptor kinase. However, the potential of Smad dephosphorylation as a regulatory mechanism of TGFbeta signaling and the identity of Smad-specific phosphatases remain elusive. Using a functional genomic approach, we have identified PPM1A/PP2Calpha as a bona fide Smad phosphatase. PPM1A dephosphorylates and promotes nuclear export of TGFbeta-activated Smad2/3. Ectopic expression of PPM1A abolishes TGFbeta-induced antiproliferative and transcriptional responses, whereas depletion of PPM1A enhances TGFbeta signaling in mammalian cells. Smad-antagonizing activity of PPM1A is also observed during Nodal-dependent early embryogenesis in zebrafish. This work demonstrates that PPM1A/PP2Calpha, through dephosphorylation of Smad2/3, plays a critical role in terminating TGFbeta signaling.

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services.

Smad proteins are intracellular signaling effectors of the TGF beta superfamily. We show that endogenous Smad2, 3, and 4 bind microtubules (MTs) in several cell lines. Binding of Smads to MTs does not require TGF beta stimulation. TGF beta triggers dissociation from MTs, phosphorylation, and nuclear translocation of Smad2 and 3, with consequent activation of transcription in CCL64 cells. Destabilization of the MT network by nocodazole, colchicine, or a tubulin mutant disrupts the complex between Smads and MTs and increases TGF beta-induced Smad2 phosphorylation and transcriptional response in CCL64 cells. These data demonstrate that MTs may serve as a cytoplasmic sequestering network for Smads, controlling Smad2 association with and phosphorylation by activated TGF beta receptor I, and suggest a novel mechanism for the MT network to negatively regulate TGF beta function.