Time-courses Satellite papers

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Satellite manuscript internal review page for Time-course Satellite papers

Welcome to the FANTOM5 Satellite review page. As discussed at the Ume and Koyo meetings, all papers will be visible to consortium members. This is to allow everyone to know what is going on, promote collaboration, carry out due process regarding co-authorship and to avoid competition. This version of the page is to cover the phase 2 satellite papers resulting from the time course analyses.

Authorship

The author list will basically be selected by the first author and the corresponding author of each satellite paper on the basis of the scientific contribution to the manuscript. Remember to include an authors contribution statement for all authors named in your manuscript (of the form AB carried out the cell isolation, SB carried out the network predictions etc.).

In addition the FANTOM5 headquarter will name RIKEN OSC members who should be co-authors for their input on each manuscript and to the entire FANTOM5 project. For those of you who have participated in previous FANTOMs you will be familiar with this process, for those new to FANTOM please look at the author lists on the satellite paper collections for FANTOM2-4. FANTOM5 headquarter is currently discussing the policy for RIKEN OSC co-authorship on the FANTOM5 satellites, but basically satellites papers will be considered on a case by case basis, and will take into account datasets used, intellectual input and facilitating technologies/analyses for each paper.

At this stage please name any authors from the OSC that you think should definitely be included as co-authors, in addition for all satellite submissions include the following term RIKEN_OSC_members as an additional author.


Updated flow for the Fantom Phase 1 and Phase 2 papers submission and manuscript formatting guidelines

With the Phase 1 and 2 main paper published, we have changed the flow for the Phase 1 and 2 manuscript submission. We have also consolidated information that was scattered in several e-mails sent to the FANTOM5 mailing list into a single document. We kindly ask everyone to stick the below flow and manuscript formatting guidelines linked in this section.

Please CC Erik Arner erik.arner@riken.jp and FANTOM5 Secretariat fantom5-secretariat@gsc.riken.jp in all correspondence connected to your paper.

General flow for satellite paper submission:

At draft stage:

1. All draft manuscripts should be entered into the wiki prior to submission - sharing these avoids internal competition and cases where co-authors are missed.

Phase1 satellite submission page: https://fantom5-collaboration.gsc.riken.jp/wiki/index.php/Satellite_submission

Phase2 satellite submission page: https://fantom5-collaboration.gsc.riken.jp/wiki/index.php/Time-courses_Satellite_papers

2. A contributions statement should be included on all manuscripts

3. Draft manuscripts should be sent to Erik Arner erik.arner@riken.jp (please CC fantom5-secretariat fantom5-secretariat@gsc.riken.jp as well) to assess RIKEN co-authorships. Each manuscript will be considered on a case by case basis and will consider, data production, optimization of mapping, data management, and establishment of the collaboration and management of the project over the past 4 years. In a few cases we also recommended additional authors from outside the RIKEN if they had provided particular critical sets of samples or co-ordinated analyses.

4. After authorship consideration by the FANTOM management you will be notified about the RIKEN authorship and also the RIKEN author who will be the contact person for communicating with the 1st author within RIKEN

5. Going through internal review (optional) If you would like your manuscript to undergo internal review, it can be organized within FANTOM consortiums. Please update the latest copy to the Satellite submission page and contact Erik Arner erik.arner@riken.jp. Please allow at least a week turnaround.

6. Be sure to follow the consortium manuscript formatting rules regarding authorship, affiliations, acknowledgements etc., as summarized in the below manuscript formatting manual with author checklist:


File:F5 satellite manuscript formatiing rules 150226.pdf


Before submission

7. Before submission to a journal, please be sure to send the manuscript to all the co-authors and get their feedback and consensus about the contents etc.


At the time of the submission/after submission

8. Please keep Erik Arner erik.arner@riken.jp, the RIKEN contact author and FANTOM5 Secretariat fantom5-secretariat@gsc.riken.jp updated about the paper progress or any change in submission status. In case of revisions, submission after rejection please be sure to send the manuscript to all the authors for confirmation. Please keep your wiki entries up to date.

9. After the paper is accepted be sure to send the proof to all the authors for the checks.

If you have any questions, please contact Erik Arner erik.arner@riken.jp(cc FANTOM5 Secretariat fantom5-secretariat@gsc.riken.jp)

Instructions

Please make a copy of the template below and enter your manuscript details.

If you are not able to edit the wiki yourself please email the secretariat with the subject line "FANTOM5_satellite", but please understand that these will be processed when we can rather than immediately. You must fill in all of the details below and provide both a PDF that contains all figures, and word doc of the main text, for reviewers to mark up directly.

Manuscripts

PUBLISHED OR ACCEPTED

Title: Transcriptional Dynamics Reveal Critical Roles for Non-coding RNAs in the Immediate-Early Response

ManuscriptID: Phase2_012
Status: PUBLISHED IN PLOS COMPUTATIONAL BIOLOGY
Abstract:  Immediate-early genes are capable of induction without de novo protein synthesis. We examine four cap analysis of gene expression (CAGE) time series datasets where the immediate-early response is induced, using data produced by the FANTOM5 project. Using a novel analysis method for time series expression data, the time course dynamics of each transcript in these large datasets are assigned to a particular kinetic signature where there is sufficient statistical support. These signatures include one that characterises the immediate-early response of mRNA transcription. Our procedure accounts for the considerable variation that is often present between biological replicates, and for differences in model complexity. This approach allows us to discover transcripts displaying expression dynamics of critical importance to cell fate decisions, even for lowly expressed transcripts such as non-coding RNAs. We identify known and novel transcripts with expression patterns that closely resemble the dynamics of genes involved in the immediate early response. Comprehensive meta-analysis of immediate-early dynamics across cell types and extracellular stimuli reveals components of a common regulatory network, on the background of a diversity of transcripts showing immediate-early dynamics specific to a particular cell type or stimulus. The response of these genes is explained by their transcriptional activation and chromatin state prior to stimulation which we obtain by integrating genome-wide data. Our method is well suited to meta-analyses: there is no requirement for transcripts to pass thresholds for significant differential expression between time points, and it is agnostic to the number of time points per dataset.
Authors: Stuart Aitken, Colin Semple, Mariko Okada-Hatakeyama, Shigeyuki Magi, Levon Khachigian, Ahmad M.N. Alhendi,  Alistair R.R. Forrest,  Piero Carninci,  Erik Arner,  Yoshihide Hayashizaki , the FANTOM Consortium.
Authors contribution statement: SA designed and performed the computational analysis. SA and CS wrote the manuscript with contributions from SM, MO, EA, AA and LK. AF, PC and YH prepared and pre-processed the CAGE libraries. All authors read and approved the final manuscript.
Datasets used: phase2 CAGE peaks
Target journal(s): Genome Research
Internal submission date:
Contact by email: colin.semple@igmm.ed.ac.uk  
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): Media:Aitken.pdf


Title: Promoter-level expression clustering identifies time development of transcriptional regulatory cascades initiated by ErbB receptors

ManuscriptID: Phase2_006
Status: PUBLISHED IN SCIENTIFIC REPORTS
Abstract: The analysis of CAGE (Cap Analysis of Gene Expression) time-course has been recently proposed to extend the understanding of the sequence of events facilitating cell state transition [main F5 time course paper] at a level of promoter regulation. To identify most prominent transcriptional regulations induced by growth factors in the human breast cancer, we apply here the CIDER analysis approach to the epidermal growth factor (EGF) or heregulin (HRG), ligands for ErbB membrane tyrosine receptors, stimulated MCF-7 CAGE time-course datasets. The analysis describes the entire regulatory chain across time, moving from the action of immediate early gene (IEG) transcription factors (TFs) to the effects of late TFs on late time-points. We identify a multi-level cascade of regulations that connects the MAPK-mediated transduction of HRG stimulus to the negative regulation of the MAPK pathway itself. The finding confirms the known primary role of FOS and FOSL1, members of AP-1 family, in shaping gene expression in response to HRG induction. Moreover, we identify a new potential regulation of DUSP5 and RARA (known to antagonize the transcriptional regulation of the estrogen receptor), by the combined interaction of FOS and FOSL1 specific to HRG response. The result indicates that a divergence in AP-1 regulation determines cellular changes of breast cancer cells stimulated by ErbB receptors.
Authors: Marco Mina, Shigeyuki Magi, Yuko Saeki, Giuseppe Jurman, ... more authors ..., Mariko Okada, Cesare Furlanello
Authors contribution statement: MR did ..., TO did ..., KE did ..., EA did ..., AL did ...
Datasets used: phase2 CAGE peaks
Target journal(s): NAR
Internal submission date:
Contact by email: Mariko Okada Cesare Furlanello
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

Title: Redefining the transcriptional regulatory dynamics in classical and alternative activated macrophage by deepCAGE transcriptomics

ManuscriptID: Phase2_005
Status: PUBLISHED IN NAR
Abstract: Classically or alternatively activated macrophages (M1 and M2, respectively) play distinct and important roles for microbiocidal activity, regulation of inflammation and tissue homeostasis. Despite this, their transcriptional regulatory dynamics are poorly understood. Using promoter-level expression profiling by non-biased deepCAGE we have studied the transcriptional dynamics of classically and alternatively activated macrophages. Transcription factor (TF) binding motif activity analysis revealed four motifs, NFKB1_REL_RELA, IRF1,2, IRF7 and TBP that are commonly activated but have distinct activity dynamics in M1 and M2 activation. We observe matching changes in the expression profiles of the corresponding TFs and show that only a restricted set of TFs change expression. There is an overall drastic and transient up-regulation in M1 and a weaker and more sustainable up-regulation in M2. Novel TFs, such as Thap6, Maff, (M1) and Hivep1, Nfil3, Prdm1, (M2) among others, were suggested to be involved in the activation processes. Additionally, 52 (M1) and 67 (M2) novel differentially expressed genes and, for the first time, several differentially expressed long non-coding RNA (lncRNA) transcriptome markers were identified. In conclusion, the finding of novel motifs, TFs and protein-coding and lncRNA genes is an important step forward to fully understand the transcriptional machinery of macrophage activation.
Authors: Sugata Roy, Sebastian Schmeier, Erik Arner, Tanvir Alam, Suraj P. Parihar, Mumin Ozturk,Ousman Tamgue, Hideya Kawaji, Michiel J.L. de Hoon1, Masayoshi Itoh1, Timo Lassmann, Piero Carninci, Yoshihide Hayashizaki, Alistair R. R. Forrest, Vladimir B.Bajic, Reto Guler, FANTOM Consortium, Frank Brombacher5*, Harukazu Suzuki*
Authors contribution statement: SR, RG, FB and HS designed the CAGE experiments. SR, FB, SS, TA, VBB and HS planned bioinformatics analysis. SR, RG prepared the samples. SS performed differential expression analysis and various analyses of the CAGE data. EA performed quality control, motif activity analysis of the CAGE data. TA and VBB performed non-coding RNA analysis. MH develops motif activity analysis pipe line. SR, RG, SP, MO, SS performed marker gene identification work. HK,TL,MI, PC, ARRL and YH responsible for management and concept in the FANTOM5 project and HK led the data control and management group in FANTOM5, SR, HS, FB, EA, RG with the help of all authors wrote and contributed to the manuscript preparation.
Datasets used: phase2 CAGE peaks
Target journal(s): NAR
Internal submission date:
Contact by email: Frank Brombacher, Roy Sugata, Harukazu Suzuki
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

Title: DeepCAGE transcriptomics reveal an important role of the transcription factor MAFB in lymphatic endothelium

ManuscriptID: Phase2_019
Status: PUBLISHED IN CELL REPORTS
Abstract: VEGF-C / VEGFR-3 signaling plays a central role in lymphatic development, regulating the budding of lymphatic progenitor cells from embryonic veins and maintaining the expression of PROX1 during later developmental stages. Notwithstanding, it is still incompletely understood how activation of VEGFR-3 is translated into expression of target gene. We used cap analysis of gene expression (CAGE) RNA sequencing to characterize the transcriptional changes invoked by VEGF-C in LECs, and to identify the transcription factors (TFs) involved. We found that MAFB, a TF involved in differentiation of various cell types, is rapidly induced and activated by VEGF-C. Functionally, MAFB induced expression of PROX1 as well as other TFs and markers of differentiated LEC, indicating a role in the maintenance of the mature LEC phenotype. Correspondingly, E14.5 Mafb -/- embryos show impaired lymphatic patterning in the back skin. This suggests that MAFB is an important TF involved in lymphangiogenesis.
Authors: Lothar C. Dieterich, Sarah Klein, Anthony Mathelier, Adriana Sliwa-Primorac, Qiaoli Ma, Young-Kwon Hong, Jay W. Shin, Michito Hamada, Marina Lizio, Masayoshi Itoh, Hideya Kawaji, Timo Lassmann, Carsten O. Daub, Erik Arner, Piero Carninci, Yoshihide Hayashizaki, Alistair R. R. Forrest, Wyeth W. Wasserman, Michael Detmar
Authors contribution statement:
Datasets used: phase2 CAGE peaks
Target journal(s): Blood or Circ Res
Internal submission date:
Contact by email: Michael Detmar
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:Dieterich et al - Mafb manuscript.pdf

Title: DeepCAGE transcriptomics identify HOXD10 as transcription factor regulating lymphatic endothelial responses to VEGF-C

ManuscriptID: Phase2_008
Status: PUBLISHED IN JOURNAL OF CELL SCIENCE
Abstract: The lymphatic vasculature plays critical roles in the maintenance of tissue fluid balance, in the uptake of dietary fats and during immune responses. Lymphatic vessels are also actively involved in promoting cancer metastasis to lymph nodes and in limiting chronic inflammatory diseases. Vascular endothelial growth factor-C (VEGF-C) represents the major lymphangiogenic factor, acting mainly via activation of VEGF receptor-3 (VEGFR-3). Thus, VEGF-C and its receptor have become targets for new therapeutic approaches to inhibit cancer metastasis and chronic inflammatory diseases. However, little is known about the downstream transcriptional mechanisms that mediate the effects of VEGFR-3 activation. Here, we aimed to identify transcription factors activated by VEGF-C/VEGFR-3 signaling in lymphatic endothelium. For this purpose, we used a mutant form of VEGF-C (VEGF-C156S), which specifically activates VEGFR-3 to stimulate lymphatic endothelial cells, and analyzed gene expression changes at multiple time points over a period of 8h using the cap analysis of gene expression (CAGE) method. We found that 84 transcription factors (TFs) were differentially expressed over the stimulation time course. Many of these TFs were known early response genes, such as EGRs, ATF3, and FOS. We confirmed up-regulation of 14 TFs that showed expression peaks between 30 and 80 min after stimulation by qPCR. To identify TFs that are specifically involved in the lymphatic endothelial cell response to VEGF-C156S, we analyzed TF binding sites in the promoters of differentially expressed genes using oPOSSUM3, and also compared our gene expression data with published expression data sets of different cell types treated with VEGF-A or EGF. These analyses revealed a small number of TFs that are specifically upregulated in lymphatic endothelial cells after VEGF-C stimulation, some of which have not been associated with lymphatic function before. We have analyzed one of these TFs, HOXD10, in more detail regarding its role in gene expression and biological function in lymphatic endothelial cells, using knockdown and overexpression systems in vitro. Of note, we found that VEGF-C induced upregulation of NR4A1 is dependent on HOXD10 expression. Furthermore, expression of eNOS was reduced in cells depleted of HOXD10, whereas HOXD10 overexpression increased eNOS levels. Based on these findings, we suggest that HOXD10 is involved in the regulation of VEGF-C responses in lymphatic endothelial cells, and affects lymphatic function via regulation of eNOS.
Authors: Sarah Klein, Lothar C. Dieterich, Anthony Mathelier, Adriana Primorac, Kim-Anh Le Cao, Hideya Kawaji, Eric Arner, Carsten Daub, ...., Michael Detmar
Authors contribution statement: SK did ..., AM did ..., LD did ..., AP did ..., KLC did ...
Datasets used: phase 2 CAGE peaks
Target journal(s): J Cell Biol?
Internal submission date:
Contact by email: Michael Detmar
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf


Title: Application of gene expression trajectories initiated from ErbB receptor activation highlights the dynamics of divergent promoter usage.

ManuscriptID: Phase2_023
Status: PUBLISHED IN PLoS ONE

Abstract: Understanding how cells change their fate in response to specific stimuli via complex transcriptional programs is an important question in biology. For MCF-7 human breast cancer cell lines, we applied gene expression trajectory models to identify the genes involved in driving cell fate transitions. We modified the trajectory models to account for the case where cells were exposed to different stimuli, in this case epidermal growth factor and heregulin, to arrive at different cell fates, i.e. proliferation and differentiation respectively. Using genome-wide CAGE time series data collected from the FANTOM 5 consortium, we used these trajectory models to identify which promoters were involved in facilitating the transition of MCF-7 cells to their specific fates versus those that changed their expression in a manner that was generic to both stimuli. Of the 1,552 promoters identified using our modeling approach, 1,091 of these promoters had stimuli-specific expression while 461 promoters had generic expression profiles over the time course. Many of these stimuli-specific promoters mapped to key regulators of the ERK signaling pathway such as FHL2. We observed that in general, generic promoters peaked in their expression early on in the time course, while stimuli-specific promoters tended to show activation of their expression at a later stage. The genes that mapped to stimulus-specific promoters were enriched for pathways that control focal adhesion, p53 signaling and MAPK signaling while generic promoters were enriched for cell death, transcription and the cell cycle. We identified 162 genes that were controlled by an alternative promoter during the time course where a subset of 37 genes had separate promoters that were classified as stimuli-specific and generic. The results of our study highlighted the degree of complexity involved in regulating a cell fate transition where multiple promoters mapping to the same gene can demonstrate quite different expression profiles.
Authors: Daniel Carbajo, Shigeyuki Magi, Masayoshi Itoh, Hideya Kawaji, Timo Lassmann3,4, Erik Arner, Alistair R.R. Forrest, Piero Carninci, Yoshihide Hayashizaki, Carsten O. Daub, the FANTOM Consortium, Mariko Okada-Hatakeyama, Jessica C. Mar
Authors contribution statement: ..
Datasets used: phase 1 human pCAGE peaks, phase 2 human CAGE peaks


Target journal(s): PLoS ONE
Internal submission date:
Contact by email: Jess Mar
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

Title: Hierarchical organisation of chromosome folding in mammalian cells

ManuscriptID: Phase2_015
Status: PUBLISHED IN MOLECULAR SYSTEMS BIOLOGY
Abstract: ...
Authors: Ana Pombo, Colin Semple, Josée Dostie, James Fraser, Carmelo Ferrai, Kelly J. Morris, Stuart Aitken, Andrea Maria Chiariello, Giovanni Laudanno, Markus Schueler, Mariano Barbieri, Tiago Rito, Meng Li, Mario Nicodemi, … OSC members
Authors contribution statement: MR did ..., TO did ..., KE did ..., EA did ..., AL did ...
Datasets used: mouse ESC-46C, day 5 and day 14 differentiation (Pombo lab samples)
Target journal(s): Nature, Nature Cell Biol, Nature Struct Biol
Internal submission date:
Contact by email: Ana Pombo
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

Title: Transcriptional switch point during hematopoietic stem cell ontogeny

ManuscriptID: Phase2_010
Status:ACCEPTED AT STEM CELLS AND DEVELOPMENT
Abstract: During mammalian embryogenesis, hematopoietic stem cells (HSCs) originate from mesoderm-derived endothelial cells in the aorta-gonad-mesonephros (AGM) region and placenta. Later, HSCs expand in fetal liver and migrate to bone marrow shortly before birth. Understanding global transcriptional regulation occurring governing HSC generation from embryonic stem/induced pluripotent stem cells and HSC expansion before transplantation is necessary for clinical therapy. To assess transcription dynamics at these stages, we performed Cap Analysis of Gene Expression (CAGE) on 10 developmental murine HSC populations isolated from the AGM region, placenta, fetal liver and bone marrow and identified 15,681 transcripts across HSC ontogeny. The HSC transcriptome underwent major changes from 9.5 to 10.5 day post-coitum (dpc) in the AGM region. Integration of co-expression data with known sequence motifs and ChIP-sequencing analysis of transcription factor binding allowed transcript-level reconstruction of gene expression networks and defined temporal changes in signaling cascades that regulate HSC maturation. Focusing on Lyl1, Myc and Lmo2 loci, we also quantified dynamic changes in transcripts encoding key regulators and identified a novel transcript emerging from the Lyl1 locus. Overall, we present a data resource of high value in understanding transcript dynamics during HSC ontogeny.

Authors: Daisuge Sugiyama, Anagha Joshi (equally-contributed), Kasem Kulkeaw, Tomoko Yokoo-Inoue,Keai Sinn Tan, Masayoshi Itoh, Sayaka Nagao-Sato, Kenzaburo Tani, Koichi Akashi, Yoshihide Hayashizaki,Harukazu Suzuki,Hideya Kawaji, Piero Caminci, Alistair Forrest,

Authors contribution statement: D.S. designed the study and co-wrote the manuscript; T.Y.I., K.K., and K.S.T. isolated HSCs and performed most experiments; K.A. and K.T. analyzed data; A.J. performed all HSC bioinformatics analysis; M. I., and S. N. S. were responsible for CAGE data production; H. K. managed data handling; H.S., P.C., Y.H. and A.R.R.F. were responsible for the FANTOM5 concept and management. A.J. analyzed and interpreted data and co-wrote the manuscript. A.R.R.F. helped with interpretation and writing of the manuscript.

Datasets used: phase 2 CAGE peaks

Target journal(s): e-Blood

Internal submission date:

Contact by email: Daisuke Sugiyama

Word document version of manuscript for editors: PDF version for general viewing (including all figs in one PDF):File:Sugiyama Joshi FANTOM submitted.pdf

Title: Transcriptional dynamics during human adipogenesis and its link to adipose morphology and distribution

ManuscriptID: Phase2_014
Status: ACCEPTED AT DIABETES
Abstract: ...
Authors: Anna Ehrlund, Jurga Laurencikiene, Niklas Mejhert, OSC_members,..., Peter Arner, Erik Arner
Authors contribution statement: MR did ..., TO did ..., KE did ..., EA did ..., AL did ...
Datasets used: phase2 human adipogenesis time course CAGE peaks
Target journal(s):
Internal submission date:
Contact by email: Anna Ehrlund, Peter Arner, Erik Arner
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

SUBMITTED

...

IN PREPARATION

Title: Cerebellum timecourse

ManuscriptID: Phase2_001
Status: ANALYSIS
Abstract: ....
Authors: Thomas Ha, Peter Zhang, Doug Swanson, OSC_members and Dan Goldowitz...
Authors contribution statement: MR did ..., TO did ..., KE did ..., EA did ..., AL did ...
Datasets used: phase2 CAGE peaks
Target journal(s): Nature Neuroscience
Internal submission date:
Contact by email: Thomas Ha, Dan Goldowitz
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

Title: LPS response

ManuscriptID: Phase2_002
Status: ANALYSIS
Abstract: ....
Authors: Kenneth Bailie, David Hume...
Authors contribution statement: MR did ..., TO did ..., KE did ..., EA did ..., AL did ...
Datasets used: phase2 CAGE peaks
Target journal(s): Nature Immunology
Internal submission date:
Contact by email: Kenneth Baillie, David Hume
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

Title: Transcriptional regulation during mineralisation of Saos-2 human osteosarcoma cells, a model for bone mineralisation

ManuscriptID: Phase2_003
Status: ANALYSIS
Abstract: ....
Authors: Margaret Davis, Kim Summers...
Authors contribution statement: MR did ..., TO did ..., KE did ..., EA did ..., AL did ...
Datasets used: phase2 CAGE peaks
Target journal(s): Maybe High but not nature
Internal submission date:
Contact by email: Kim Summers, Margaret Davis
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

Title: Myoblast differentation

ManuscriptID: Phase2_004
Status: ANALYSIS
Abstract: ....
Authors: Beatrice Bodega, Tim Ravasi, Valerio Orlando...
Authors contribution statement: MR did ..., TO did ..., KE did ..., EA did ..., AL did ...
Datasets used: phase2 CAGE peaks
Target journal(s): ...
Internal submission date:
Contact by email: Beatrice Bodega, Valerio Orlando, Tim Ravasi
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf


Title: Chromatin at the boundaries of pluripotency and differentiation

ManuscriptID: Phase2_007
Status: ANALYSIS
Abstract: Understanding how the chromatin environment and topology direct stem cell maintenance and cell fate decisions is key to understanding early human development. We address this by analysis of CAGE data obtained from human pluripotent stem cells, induced stepwise to differentiate into the ectodermal lineage (neurons and melanocytes) and the mesodermal linage (cardiomyocytes and CD34+ HSC). We identify a small number of specific master enhancer sequences that initiate exit from the pluripotent state and a separate set of enhancers that act at defined temporal windows to direct these neuroectodermal and mesodermal lineage fate decisions. We further demonstrate that enhancer RNAs and non-coding RNAs derived from such enhancers are present at/direct cohesin-mediated chro¬matin loops and long-range interactions between regulatory elements. Indeed, deletion of such master enhancers using TALEN based approaches or shRNA mediated knockdown of eRNA or enhancer ncRNAs abolishes both these higher order chromatin structures and affects the fate decisions of human pluripotent stem cells. Our data offer insight into the principles that control genome plasticity and govern early fate decisions during human development.
Authors: Sample providers are: Ernst Wolvetang and Christine Wells, Rolf Swoboda and Meenhard Herlyn, Kim Summers, Christine Mummery and Robert Passier .. Bioinformaticians (so far) are Robin Andersson and Albin Sandelin; Boris Lenhard; IsMara team; Colin Semple; Moreton Rye and Finn Drables; Owen Rackham and Julian Gough...
Authors contribution statement: ...
Datasets used: phase2 CAGE peaks
Target journal(s): Nature, Nature genetics, Cell Stem Cell or Nature Neuroscience
Internal submission date:
Contact by email: Albin Sandelin Christine Wells
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF):  File:Chromatin at the boundaries of pluripotency and differentiation-1.pdf

NOTE: Some key questions:
Can we link the loss of ES enhancers or increased activity of lineage specific enhancers with H3K9me2 (CHIP validation?), H3K27ac/H3K4me1 state or H3K27me3 of LOCKS (large organised chromatin domains of H3K9me2 that increase in size and abundance (from 4% to at most 46% genome coverage) from ESCs to differentiated cells).

Are the enhancers controlling specific gene clusters lacking or acquiring histone H3K4me3 what is the overlap with the LADS identified by DAMID (within neuronal diff timecourse)?

Why is this analysis novel and potentially high-impact? First demonstration of Cis-acting enhancers necessary for expression of pluripotency network, across multiple cell lines and multiple differentiation lineages.

First genome-wide analysis of Enhancers that drive differentiation along neuroectoderm or mesodermal lineages (or are they driven? what comes first?)

First analysis of Long-range enhancers that influence sets of pluripotency and/or differentiation genes

First evidence of chromatin boundaries by merging structural data and CAGE data (be interesting to look at nc-RNA overlap with these elements).

Transcription factor networks predicted from enhancer and promoter maps show (common?) events in the early steps of differentiation. In vitro modelling of the differentiation hierarchy

Any evidence of bivalency (Nucleosome pausing? ENCODE + CAGE)


Title: Erythroid differentiation timecourse

ManuscriptID: Phase2_009
Status: ANALYSIS
Abstract: Elucidating key regulators of hemopoiesis is critical to designing better treatments and new therapies for diseases such as anemia and leukemia. The FANTOM5 deepCAGE tag sequencing of the murine J2E cell line will provide a dynamic analysis of gene expression during erythroid differentiation. A key strength of this time course is that we have many early time points which will enable correlation of gene expression with early functional events, as well as identification of key initiators of erythroid differentiation including changes in enhancer usage, TF dynamics, epigenetic regulators and miRNAs. No comprehensive dynamic analysis of these very early events in erythropoiesis has been undertaken. J2E cells can be induced with the hormone erythropoietin to biochemically and morphologically differentiate down the erythroid pathway with a portion of cells becoming reticulocytes. Initial analysis of the data indicate that important transcription factors (eg GATA-1, Fog1, Klf1, Nfe2) heme enzymes (eg Alas2, Cpox, Ppox, Uros, Urod, Fech), globin genes and cytoskeletal genes are induced as expected, suggesting that this time course is a good representation of in vivo events. Ongoing analysis seeks to i) identify early response genes for erythropoiesis ii) define expression based gene clusters representative of different time points, iii) correlate gene expression with enhancer usage, iv) identify dynamic (ie across time points) networks of gene expression and v) compare normal erythroid gene expression networks to leukemia cell lines.
Authors: Louise Winteringham, Peter Klinken, Robin Andersson,Ilka Hoof, Albin Sandelin, Kenny Baillie, Tom Freeman, Michael Rehli, Peter Pemberton-Ross, Sarah Baker, Martin Taylor,Pal Saetrom, Erik Arner, Carston Daub, Alistair Forest, Hideya Kawaji, Piero Carninci,Yoshihide Hayashizaki
Authors contribution statement:
Datasets used: phase2 CAGE peaks
Target journal(s): Nature Cell Biology/ Molecular Cell
Internal submission date:
Contact by email: Louise Winteringham
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf


Title: Smooth muscle cells with Fgf2 or IL1

ManuscriptID: Phase2_011
Status: ANALYSIS
Authors: Levon Khachigian, more authors
Authors contribution statement: MR did ..., TO did ..., KE did ..., EA did ..., AL did ...
Datasets used: phase1 CAGE peaks
Target journal(s): TBD
Internal submission date:
Contact by email: Levon Khachigian
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf


Title: Transcriptional regulation of epigenetic regulators

ManuscriptID: Phase1_013
Status: ANALYSIS
Abstract: We will map the expression profiles of 505 epigenetic regulators in the different time courses. In addition we will analyze the transcriptional regulation of the regulators in different cell/tissue types.
Authors: Yulia Medvedeva, Andreas Lennartsson and Finn Drablos
Authors contribution statement: MR did ..., TO did ..., KE did ..., EA did ..., AL did ...
Datasets used: phase2 Time courses
Target journal(s):
Internal submission date:
Contact by email: Finn Drabløs Andreas Lennartsson Yulia Medvedeva
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

Title: Polycomb repressed genes are transcribed in mouse ES cells.

ManuscriptID: Phase2_016
Status: ANALYSIS
Abstract: ...
Authors: Ana Pombo, Boris Lenhard, Kelly J. Morris, Ines de Santiago, Nathan Harmston, Tiago Rito, Markus Schueler, Emily Brookes, … OSC members
Authors contribution statement: MR did ..., TO did ..., KE did ..., EA did ..., AL did ...
Datasets used: mouse ESC-OS25, ESC-OS25+amanitin, ESC-OS25+flavopiridol, ESC-OS25-Exosc knockdown, ESC-Ert2 Ring1B knockout (Pombo lab samples)
Target journal(s): Cell Stem Cell
Internal submission date:
Contact by email: Ana Pombo
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

Title: Genome-wide transcriptome profiling of liver sinusoidal endothelial cells and hepatocytes during mouse liver regeneration

ManuscriptID: Phase2_017
Status: DRAFT
Abstract: ...
Authors: Xian-Yang Qin, Mitsuko Hara, Hideki Tatsukawa, Erik Arner, Feifei Wei, Jun Kikuchi, Yang Zeng, Hideko Sone, Harukazu Suzuki, Piero Carninci, Yoshihide Hayashizaki, the FANTOM consortium, Alistair R. R. Forrest and Soichi Kojima
Authors contribution statement: MR did ..., TO did ..., KE did ..., EA did ..., AL did ...
Datasets used: liver regeneration samples
Target journal(s):
Internal submission date:
Contact by email: CHANGETHIScorresponding1 CHANGETHIScorresponding2
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

Title: Network-based identification of dynamic regulatory patterns by combined promoter expression clustering and motif enrichment analysis

ManuscriptID: Phase2_018
Status: ANALYSIS
Abstract: We introduce a novel approach based on promoter expression clustering and motif enrichment to provide a comprehensive regulatory map of Fantom 5 phase 2 time-courses. To identify dynamic regulatory patterns we endow the Complexity Invariant Dynamic Time Warping (CID-DTW) distance into a general hierarchical time series clustering pipeline, then selecting prototype shapes of biological relevance with the MEME motif enrichment analysis. Patterns identified are consistent with those defined by the rule-based methodology. In particular, the method has been used to identify regulatory roles of FOSL1 and ESR1 in MCF7-HRG, MCF7-EGF1, and MSC-Adipo differentiation time-courses. As an application, we infer complete regulatory networks and define a similarity structure between networks for different time-course data.
Authors: Marco Mina, ..., Cesare Furlanello
Authors contribution statement:
Datasets used: MCF7 HRG, MCF7 EGF1, MSC-Adipo differentiation phase2 time-courses
Target journal(s):
Internal submission date:
Contact by email: Marco Mina
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

Title: Detection of the functional antisense transcripts during adipocyte/osteoblast differentiation in mouse bone marrow-derived stromal cell ST2

ManuscriptID: Phase2_020
Status: ANALYSIS
Abstract: ...
Authors: Yutaka Nakachi, Yosuke Mizuno, Yoshimi Tokuzawa, Yzumi Yamashita-Sugahara, Yukiko Kanesaki-Yatsuka, Yasushi Okazaki, et al.
Authors contribution statement: YN did , YM did ..., YT did ..., YYS did ..., YKY did ..., YO did ...
Datasets used: phase2 CAGE peaks
Target journal(s):
Internal submission date:
Contact by email: Yasushi Okazaki,Yutaka Nakachi,Yosuke Mizuno
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

Title: Epigenetic activity improves the co-regulation of nearby transcripts

ManuscriptID: Phase2_021
Status: Submitted to Biosystems September 2015
Abstract: Epigenetic networks aim to mimic the epigenetic layer observed in biological gene regulatory systems to improve the efficiency of general network models. However, it is currently not clear whether the type of epigenetic contribution assumed by such networks represent the real epigenetic events observed in a cell. Epigenetics control cell-type specific gene expression and cell differentiation in all multicellular organisms by partitioning the genome into epigenetic domains with various transcriptional properties. It is thus conceivable that coordinated epigenetic gene control would also lead to correlated expression patterns assumed by epigenetic network models. To investigate whether the term “epigenetic network" can be justified, we have analyzed transcript expression data from a cell differentiation time series experiment to determine if transcripts in epigenetically active regions have more similar expression profiles than have other transcripts. By analyzing three separate marks of epigenetically active regions, we find improved correlation between epigentically active transcripts enriched for the same epigenetic mark. Importantly, close transcripts within active regions have a higher correlation than have distant transcripts. Moreover, this correlation is higher than what can be explained by genomic proximity alone for regions shorter than 50 kbp.By integrating epigenetic and transcript expression data from a time series differentiation study, we show that transcripts within spatially proximal epigenetically active regions are highly correlated. The results confirm that the epigenetic contribution assumed by epigenetic networks is present in real biological systems, and should thus facilitate the construction of epigenetic networks for such systems.
Authors: Alexander Turner, Finn Drabløs, Pål Sætrom, Erik Arner, Masayoshi Itoh, Hideya Kawaji, Timo Lassman, Susan Zabierowski, Piero Carninci, Alistair R.R. Forrest, Yoshihide Hayashizaki, The FANTOM Consortium and Morten Rye
Authors contribution statement: AT performed the analysis and drafted the manuscript; FD conceived the idea, drafted the manuscript and revised it critically for important intellectual content; PS drafted the manuscript and revised it critically for important intellectual content; EA was responsible for CAGE data quality control; MI was responsible for CAGE data production; HK managed the data handling; TL performed tag mapping; SZ produced the samples; PC, ARRF, YH and FC are responsible for FANTOM5 management and concept; MR conceived the idea, performed the analysis and drafted the manuscript. All authors read and approved the final manuscript.
Datasets used: phase 2 human_H9 time series
Target journal(s): Current: Biosystems
Internal submission date: March 2015
Contact by email: Morten Rye Finn Drabløs
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:Satellite draft 021.pdf

Title: Investigation of protein coding sequence exclusion by alternative promoter usage across the human body

ManuscriptID: Phase2_022
Status: Manuscript being written

Abstract: ...TBD
Authors: Berit Lilje, Wenbo Dong, Anderas Lennartsson, Albin Sandelin
Authors contribution statement: BL and AS analyzed data, WB and AL made validations
Datasets used: phase 1 human pCAGE peaks, phase 2 human CAGE peaks


Target journal(s): Genome Res, Genome Biology
Internal submission date:
Contact by email: [1]
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

Title: Identify the protective and subversive mechanisms of macrophage genes in tuberculosis infection by deep CAGE

ManuscriptID: Phase2_024
Abstract: ...
Authors: sugata Roy, sebastian Schmeier, Erik Arner, Reto Guler, Frank brombacher, Harukazu suzuki
Authors contribution statement: MR did ..., TO did ..., KE did ..., EA did ..., AL did ...
Datasets used: phase2 CAGE peaks
Target journal(s): Nature Immunology
Internal submission date:
Contact by email: mailto:fbrombac@mweb.co.za,roy@gsc.riken.jp,harukazu@gsc.riken.jp Frank Brombacher, Roy Sugata, Harukazu Suzuki
Word document version of manuscript for editors: File:ChangeThisToYourFilename.doc
PDF version for general viewing (including all figs in one PDF): File:ChangeThisToYourFilename.pdf

Title: The Mouse Enhancer-ome during development

ManuscriptID: Phase2_025
Abstract: No abstract yet. The idea is to present the mouse enhacner data (based on CAGE) which has never been shown from the main papers as a resource, focusing in particular on the developmental time points(since these are not covered in human), with some modelling applied. ...
Authors: Kristoffer Vitting-Seerup, Maria Dalby, Erik Arner, Hans Ienescu (and more), Piero Carninci, Robin Anderson, Albin Sandelin + collaborators welcome
Datasets used: phase1+2 CAGE peaks, phase1+2 CAGE CTSSs
Target journal(s): Unclear - depends on results
Internal submission date:
Contact by email: [2]
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Title: Copy and Edit This Template

ManuscriptID: Phase2_0X [INCREMENT THIS!]
Abstract: ...
Authors: MR, TO,KE, EA, AL
Authors contribution statement: MR did ..., TO did ..., KE did ..., EA did ..., AL did ...
Datasets used: phase1 CAGE peaks
Target journal(s):
Internal submission date:
Contact by email: [3]
Word document version of manuscript for editors: File:XXXYOUR.doc
PDF version for general viewing (including all figs in one PDF): File:XXXYOUR.pdf

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