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1.  Division of labour between Myc and G1 cyclins in cell cycle commitment and pace control 
Nature Communications  2014;5:4750.
A body of evidence has shown that the control of E2F transcription factor activity is critical for determining cell cycle entry and cell proliferation. However, an understanding of the precise determinants of this control, including the role of other cell-cycle regulatory activities, has not been clearly defined. Here, recognizing that the contributions of individual regulatory components could be masked by heterogeneity in populations of cells, we model the potential roles of individual components together with the use of an integrated system to follow E2F dynamics at the single-cell level and in real time. These analyses reveal that crossing a threshold amplitude of E2F accumulation determines cell cycle commitment. Importantly, we find that Myc is critical in modulating the amplitude, whereas cyclin D/E activities have little effect on amplitude but do contribute to the modulation of duration of E2F activation, thereby affecting the pace of cell cycle progression.
The transcription factor E2F is critical for determining cell proliferation. By monitoring E2F activity in single cells throughout the cell cycle, Dong et al. provide evidence that Myc and G1 cyclin/CDKs regulate different aspects of E2F temporal dynamics, resulting in distinct phenotypic outputs.
PMCID: PMC4164785  PMID: 25175461
2.  Cross-Platform Prediction of Gene Expression Signatures 
PLoS ONE  2013;8(11):e79228.
Gene expression signatures can predict the activation of oncogenic pathways and other phenotypes of interest via quantitative models that combine the expression levels of multiple genes. However, as the number of platforms to measure genome-wide gene expression proliferates, there is an increasing need to develop models that can be ported across diverse platforms. Because of the range of technologies that measure gene expression, the resulting signal values can vary greatly. To understand how this variation can affect the prediction of gene expression signatures, we have investigated the ability of gene expression signatures to predict pathway activation across Affymetrix and Illumina microarrays. We hybridized the same RNA samples to both platforms and compared the resultant gene expression readings, as well as the signature predictions. Using a new approach to map probes across platforms, we found that the genes in the signatures from the two platforms were highly similar, and that the predictions they generated were also strongly correlated. This demonstrates that our method can map probes from Affymetrix and Illumina microarrays, and that this mapping can be used to predict gene expression signatures across platforms.
PMCID: PMC3828325  PMID: 24244455
3.  Network calisthenics 
Cell Cycle  2011;10(18):3086-3094.
Stimulation of quiescent mammalian cells with mitogens induces an abrupt increase in E2F1–3 expression just prior to the onset of DNA synthesis, followed by a rapid decline as replication ceases. This temporal adaptation in E2F facilitates a transient pattern of gene expression that reflects the ordered nature of DNA replication. The challenge to understand how E2F dynamics coordinate molecular events required for high-fidelity DNA replication has great biological implications. Indeed, precocious, prolonged, elevated or reduced accumulation of E2F can generate replication stress that culminates in either arrest or death. Accordingly, temporal characteristics of E2F are regulated by several network modules that include feedforward and autoregulatory loops. In this review, we discuss how these network modules contribute to “shaping” E2F dynamics in the context of mammalian cell cycle entry.
PMCID: PMC3218619  PMID: 21900750
E2F; dynamics; feedback; feedforward; network; DNA replication
4.—the database of the Drosophila RNAi screening center: 2012 update 
Nucleic Acids Research  2011;40(Database issue):D715-D719.
FlyRNAi (, the database and website of the Drosophila RNAi Screening Center (DRSC) at Harvard Medical School, serves a dual role, tracking both production of reagents for RNA interference (RNAi) screening in Drosophila cells and RNAi screen results. The database and website is used as a platform for community availability of protocols, tools, and other resources useful to researchers planning, conducting, analyzing or interpreting the results of Drosophila RNAi screens. Based on our own experience and user feedback, we have made several changes. Specifically, we have restructured the database to accommodate new types of reagents; added information about new RNAi libraries and other reagents; updated the user interface and website; and added new tools of use to the Drosophila community and others. Overall, the result is a more useful, flexible and comprehensive website and database.
PMCID: PMC3245182  PMID: 22067456
5.  Differential requirement for STAT by gain-of-function and wild-type receptor tyrosine kinase Torso in Drosophila 
Development (Cambridge, England)  2002;129(18):4241-4248.
Malignant transformation frequently involves aberrant signaling from receptor tyrosine kinases (RTKs). These receptors commonly activate Ras/Raf/MEK/MAPK signaling but when overactivated can also induce the JAK/STAT pathway, originally identified as the signaling cascade downstream of cytokine receptors. Inappropriate activation of STAT has been found in many human cancers. However, the contribution of the JAK/STAT pathway in RTK signaling remains unclear. We have investigated the requirement of the JAK/STAT pathway for signaling by wild-type and mutant forms of the RTK Torso (Tor) using a genetic approach in Drosophila. Our results indicate that the JAK/STAT pathway plays little or no role in signaling by wild-type Tor. In contrast, we find that STAT, encoded by marelle (mrl; DStat92E), is essential for the gain-of-function mutant Tor (TorGOF) to activate ectopic gene expression. Our findings indicate that the Ras/Raf/MEK/MAPK signaling pathway is sufficient to mediate the normal functions of wild-type RTK, whereas the effects of gain-of-function mutant RTK additionally require STAT activation.
PMCID: PMC3090254  PMID: 12183376
Drosophila; Receptor tyrosine kinase (RTK); Torso; STAT
6.  A case study of the reproducibility of transcriptional reporter cell-based RNAi screens in Drosophila 
Genome Biology  2007;8(9):R203.
A second generation dsRNA library was used to re-assess factors that influence the outcome of transcriptional reporter-based whole-genome RNAi screens for the Wnt/Wingless (wg) and Hedgehog (hh)-signaling pathways.
Off-target effects have been demonstrated to be a major source of false-positives in RNA interference (RNAi) high-throughput screens. In this study, we re-assess the previously published transcriptional reporter-based whole-genome RNAi screens for the Wingless and Hedgehog signaling pathways using second generation double-stranded RNA libraries. Furthermore, we investigate other factors that may influence the outcome of such screens, including cell-type specificity, robustness of reporters, and assay normalization, which determine the efficacy of RNAi-knockdown of target genes.
PMCID: PMC2375041  PMID: 17903264
7.  FlyRNAi: the Drosophila RNAi screening center database 
Nucleic Acids Research  2005;34(Database issue):D489-D494.
RNA interference (RNAi) has become a powerful tool for genetic screening in Drosophila. At the Drosophila RNAi Screening Center (DRSC), we are using a library of over 21 000 double-stranded RNAs targeting known and predicted genes in Drosophila. This library is available for the use of visiting scientists wishing to perform full-genome RNAi screens. The data generated from these screens are collected in the DRSC database () in a flexible format for the convenience of the scientist and for archiving data. The long-term goal of this database is to provide annotations for as many of the uncharacterized genes in Drosophila as possible. Data from published screens are available to the public through a highly configurable interface that allows detailed examination of the data and provides access to a number of other databases and bioinformatics tools.
PMCID: PMC1347476  PMID: 16381918

Results 1-7 (7)