Satellite papers

Instructions

Below you can find the list of satellite paper proposals collected in the February meeting. Please add the following information to each of the proposals

• Check the title
• provide brief outline of the proposal
• add/remove your name in case you are interested to work on this satellite paper

Proposal for satellites papers 2/25/2011 Purpose: list up potential satellites; avoid redundancies, make better papers Figure out potential titles to discuss how to negotiate with specific journals.

Add a set of sentences (mini abstract) on the wiki and write an abstract

Bioinformatics analysis methods

Normalization and clustering issues

• Outline: bla
• Group members: Tom Freeman

Modulation of gene expression (Jess Mar)

• Outline: bla
• Group members: xxx, yyy, zzz

Expanding transcriptional reg. networks (Vlad)

• Outline: bla
• Group members: xxx, yyy, zzz

Tag clusterin in helicos CAGE (Cesare)

• Outline: bla
• Group members: xxx, yyy, zzz

Computational methods for networks comparisons (cesare)

• Outline: bla
• Group members: FBK (C. Furlanello, G: Jurman, ...) 

Tool to make the promoter subsets at will (do not ask us datasets!) (Albin)

• Outline: bla
• Group members: xxx, yyy, zzz

Delve tag mapping paper (Timo L)

• Outline: Methods paper on Delve: a probabilistic read mapper.
• Group members: Timo Lassmann, Carsten Daub

Classification of CAGE peaks (Timo L)

• Outline: Deeply sequenced CAGE libraries capture signals on many non-promoter regions. The purpose of this paper is to describe a strategy to separate TSS from non-TSS CAGE peaks (see: Media:CAGE_classification.pdf). Preliminary work suggest that further sub-classicifation of promoters based on the shape of the CAGE signal is possible (see: Media:Brood_october_2010.pdf).
• Group members: Timo Lassmann, Ben Brown, Colin Semple

Peak finder-noise elimination contest paper (all runners)

• Outline: bla
• Group members: xxx, yyy, zzz

Genomics-broad scale analysis

• Outline: bla
• Group members: xxx, yyy, zzz

Alternative TSS in cancer relevant to biomarkers (Win Hide)

• Outline: bla
• Group members: xxx, yyy, zzz

Impact of alternative promoters on biology of genes (Albin)

• Outline: bla
• Group members: xxx, yyy, zzz

How much do we need to sequence? Complexity of the transcriptome (Albin)

• Outline: bla
• Group members: xxx, yyy, zzz

Revised analysis of zinc finger proteins (Tim Ravasi, David Hume)

• Outline: bla
• Group members: xxx, yyy, zzz

Identification of distal regulation elements: role of enhancers in differentiation (Carsten, Boris, Ana P, Jose, YH)

• Outline: bla
• Group members: xxx, yyy, zzz

miRNA promoters (Hideya K, Eivind Al, )

• Outline: bla
• Group members: xxx, yyy, zzz

CAGE tags on Pigs: Gain and loss of promoters (David Hume) [satellite of the pig genome]

• Outline: bla
• Group members: xxx, yyy, zzz

Regulatory transcription outside canonical promoters (Boris)

• Outline: bla
• Group members: xxx, yyy, zzz

Transcription initiation in embryo development (Boris)

• Outline: bla
• Group members: xxx, yyy, zzz

Promoters with multiple TSS configuration-multiple ways to use the same promoters (Boris, Kawaji)

• Outline: bla
• Group members: xxx, yyy, zzz

Link Fantom 5 to genetic datasets (Peter Heutink; Juha K)

• Outline: Genome Wide Association Studies (GWAS) have been very succesfull in identifying new risk loci for multifactorial human disease. It has however been very difficult to identify the true biologically relevant variant. GWAS studies in general do not directly test the unknown causal variant but a variant that is in Linkage Disequilibrium with the causal variant. Studies to identify the causal variants are complicated by the observation that most signals from GWAS studies point to non-coding regions of the genome for which the functions are currently unknown. The dataset generated by FANTOM5 now allows to investigate the regions around the association signal for functional elements involved in transcription.

Research method: We have developed a statistical method to delineate the critical region for GWAS loci (Bochdanovits et al. Submitted). We aim to use this method on all publically available GWAS datasets in order to obtain the boundaries of identified GWAS loci. We will then superinpose these genomic region on FANTOM5 data from relevant tissues/celltypes for the disease and identify possible promoters. By using data from the 1000 Genomes project we will investigate if genomic variation exists in the identified promoters. These variants can then be tested for functional effects in cellular reporter assays.

• Group members: Peter Heutink, Juha Kere, Zoltan Bochdanovits and ......please sign up if you are interested.
  

Methylation effect on TFBS and expression (Yulia)

• Outline: It's commonly accepted that DNA methylation of a promoter repress transcription of this gene in normal tissues. Recently, a class of actively expressed genes having relatively methylated promoters has been discovered. The purpose of this research is to explore the idea that DNA methylation effects CG-rich TFBS, preventing TF from binding to DNA, and therefore represses transcription.

• Group members: Yulia Medvedeva

Comparison of different types/feature of promoters and genome features to study specific differences (Yulia)

• Outline: bla
• Group members: xxx, yyy, zzz

Multiple genomics analysis on multiple datasets (Haru) Extension of the validation?

• Outline: bla
• Group members: xxx, yyy, zzz

Prediction of cell transformation states (Win Hide)

• Outline: bla
• Group members: xxx, yyy, zzz

Convergent evolution of retrotransposon promoters (Geoff)

• Outline: Following the model for the anti-apoptosis gene NAIP (Romanish et al., PLoS Genetics, 2007), we will start by screening the mouse and human genomes for instances where two different retrotransposons occupy the same or similar location in protein-coding genes (e.g. an Alu in human, a B2 in mouse). If this happens frequently enough to be interesting, we will overlay the F5 data onto the "convergent" retrotransposons to see how many are transcribed, what role they may have in regulation (e.g. Lunyak et al., Science, 2007) and if the events are more common for some pathways than others (e.g. in embryogenesis or brain development).
  
• Group members: Geoff, Piero
  

Alternative TSS and alternative splicing (Nicolas)

• Outline: bla
• Group members: xxx, yyy, zzz

Chimaeric RNA and 3D structure (if it works) (Nicolas)

• Outline: bla
• Group members: xxx, yyy, zzz

Annotation of genes involved in biochemical, metabolic processes and signature for processes-for instance signature for tumors – expression based GO terms (Tom Freeman) (Richard Baldarelli, Jackson and GO groups) (David Hume)

• Outline: bla
• Group members: xxx, yyy, zzz

Blood group: fill in the holes, more discussion

Granulopoiesis analysis (Andreas Lenn.+Erik Arner)

• Outline: bla
• Group members: xxx, yyy, zzz

Eritropoiesis (Peter K)

• Outline: bla
• Group members: xxx, yyy, zzz

HSC (Sugiyama san)

• Outline: bla
• Group members: xxx, yyy, zzz

Macrophages (DH)

• Outline: bla
• Group members: xxx, yyy, zzz

Subpopulations T cells and monocytes (Michael R)

• Outline: bla
• Group members: xxx, yyy, zzz

Brain groups 4 papers Other priority areas in brain: discuss other brain and diseases (YH)

Evolution gene expression in vertebrates Martin + Peter Heutink

• Outline: Study the evolution of gene expression combining insights from each of the following:
  • Gene/transcript level changes in expression (and estimating it's constraint/diversification).
  • TSS/promoter turnover: orthologous genes using non-orthologous promoters, or changes in promoter-preference for one cell type between species.
  • Sequence evolution of core promoters and distant regulatory blocks correlated with changes in gene expression.
• Focus of the paper on the well matched cells between ((Human, (Macaque?)),(Mouse, Rat),Dog),Chicken) for which we have hCAGE data. (Cell types: Hepatocytes, Aortic smooth muscle cells, mesenchymal stem cells).
• Group members: Martin Taylor, Peter Heutink, Alison Meynert
• Details: Evolution in gene expression.

Transcriptional constrains seq evolution [Martin+Michiel talk]

• Outline: [Michiel:] Network analysis across organisms & evolution of regulatory networks, in particular of developmental networks. Are there any subnetworks particularly conserved between organisms? What does this tell us about the functional importance and relevance of specific subnetworks? Do we see any recurring patterns in the network (Uri Alon-type feed-forward loops)? What are the conservation patterns and rates of divergence of transcription factors and specific regulatory relations? Do we see turnover of TFBSs, or do we see conservation of TFBSs in alignments? This can be applied specifically to brain, or more generally to all CAGE samples. TFBS prediction in Neanderthal compared to Homo sapiens would be really cool.
• Group members: Martin, Michiel, Peter Heutink
• Martin's and Michiel's idea for this paper may overlap or may be complementary to each other; we need to discuss this. This may end up as two satellite papers or one integrated one.

Tfbs turnover in liver (integrate with ChIP seq) Martin

• Outline: Integration of cross-species ChIP-seq data in liver with proximal CAGE tag cluster responses in the same species. Data on liver ChIP-seq for the transcription factors HNF1A and CEBPA in human/mouse/dog/(chicken) Schmidt et al, Science 2010 has been obtained. The questions we can address with this study are:
  • Are conserved binding sites more likely than non-conserved sites to elicit a local, hepatocyte specific ranscriptional response? (Use CEBPA non-expressing cells to generate a background model of proximal transcriptional responses). This could be used to estimate "functional turnover" as opposed to the "binding turnover" as reported by Duncan Odom.
  • Does hepatocyte specific expression (around binding sites) segregate through species lineages with the experimentally defined binding site?
  • If there is apparent turn-over of binding sites, is the pattern of local responsive transcription conserved?
  • Do we see conservation of hepatocyte specific transcriptional responses even in the absence of binding site conservation?
• Group members: Martin Taylor, Alison Meynert

Disease paper (brain): human post mortem, … comparison healthy-disease Peter Heutink + Gustincich group

• Outline: bla
• Group members: xxx, yyy, zzz

Rett syndrome and visual cortex Alka

• Outline: bla
• Group members: xxx, yyy, zzz

Genomic architecture in 3 genes involved in Rett syndrome Alka

• Outline: bla
• Group members: xxx, yyy, zzz

Genomic architecture of neurodegenerative disease (Gustincich talk P.H., etc.)

• Outline: bla
• Group members: xxx, yyy, zzz

Others

Olfactory receptors

• Outline: Promoters of Olfactory receptors (ORs) are still poorly documented. We have an unpublished promoter list for mouse, and CAGE libraries from human olfactory mucosa will be made. We will identify the promoters of the human ORs and analyse their structure. Many ORs have alternative promoters and this is a potential example for the promotorome paper. Human-specific OR promoters might be found. There is evidence of expression of the ORs outside the mouse and human olfactory mucosa, and this satellite paper will report this. Experiments to find a ligand and propose a function may be carried out. More information on the page: Olfactory receptors.
• Group members: Charles Plessy, Giovanni Pascarella, Stefano Gustincich and others, but I am too shy to add their name without asking.

Cell-Cell communicatome (Al forrest)

• Outline: bla
• Group members: xxx, yyy, zzz

Drugable cells: drug targets (Al Forrest)

• Outline: bla
• Group members: xxx, yyy, zzz

Definition of stem or precursors relationship (Claudio Schneider)

• Outline: bla
• Group members: xxx, yyy, zzz

Gene regulation in cells of connective tissues (Vlad, Kim)

• Outline: bla
• Group members: xxx, yyy, zzz

Transdifferentiation and network rewiring (Haru; WP6 + others) POTENTIAL main paper for later stage

• Outline: bla
• Group members: xxx, yyy, zzz

Network in cancer (Rama, win’s group)

• Outline: bla
• Group members: xxx, yyy, zzz

Regulatory network in cell lineage tree (Carsten wp5)

• Outline: bla
• Group members: xxx, yyy, zzz

Determination of conserved CAGE (Vlad)

• Outline: bla
• Group members: xxx, yyy, zzz

Promoting human uniqueness: human-specific promoters of regulatory lncRNA genes drive cis- and trans-regulation. (LL)

• More information, anticipated Abstract, Definitions, Plan of Work at: Regulatory lncRNAs: 'promoting' human uniqueness
  
• Outline: In FANTOM3, we described complex loci -- sense-antisense pairs, bidirectional promoters, and gene chains -- prevalent in mammalian genomes. These complex loci often contain long non-coding RNA (lncRNA) genes not conserved between mouse and human. Now in FANTOM5, our goal is to functionally characterize the specific contribution of non-conserved sequences in human, particularly promoters of lncRNA genes, to gene regulation at complex loci. We will reach this goal by: 
  

1. identifying all "human-specific" (definition = primate-specific; thus absent in the F5 nonhuman species) promoters in CAGE and CAGEscan data.
   
2. using Cluster Annotation from the F5 main paper/s to find all lncRNA genes whose promoters are human-specific.
   
3. determining which lncRNA genes with human-specific promoters are in complex loci, as defined in the first sentence of this Outline.
   
4. testing each complex locus from #4 for the existence of a unique cis-regulatory expression signature (simple e.g.: all genes in the complex locus are on, all off, or some on and specific others off) that corresponds to a particular, well-defined cell type, tissue type, or steady state. Signatures are defined both by an expression pattern and by an adjacency, overlap, and specific order / orientation of the co-expressed genes neighboring along the genome.
   
5. determining whether, and how, each complex-locus steady-state-specific expression signature is dependent upon the human-specific promoter of the lncRNA within that signature. (Implementation details are at: Regulatory lncRNAs: 'promoting' human uniqueness ) 
   
6. performing, for lncRNAs of exceptional interest from #5, reverse-genetic experiments in cell culture to validate whether the human-specific promoter of the lncRNA really has a regulatory impact that contributes to defining a particular steady state. (Note: we would need the OSC's direct help with wet-lab validations. Let's discuss.) 
   
7. defining the unique functional proteome space (e.g. gene ontologies? positive selection? brain genes? etc) cis-regulated by human-specific lncRNA promoters.
   
8. finally, deriving a multidimensional unified cis- and trans-regulatory network that describes human-specific and lncRNA-mediated gene regulation in specific cellular states. (Definition of such a network is at: Regulatory lncRNAs: 'promoting' human uniqueness )
   

• Group members: Leonard Lipovich, Yulia Medvedeva (inviting you to join - please confirm), Vlad Bajic (inviting you to join - please confirm), Jess Mar (inviting you to join - please confirm), and I am also too shy to name (or invite) potential others. Please email me or the F5 list, or please just add yourselves to this page, if you would like to join forces on this.

Using single direction promoter ti eliminate noise (Yulia)

• Outline: bla
• Group members: xxx, yyy, zzz

Specific transcript (Human) regulation and what are nover TF in human (Haru)

• Outline: bla
• Group members: xxx, yyy, zzz

Identification of TFBS by de novo methods (Vlad; Boris)

• Outline: bla
• Group members: xxx, yyy, zzz

Predicted homotypic clusters and motif prediction (Yulia)

• Outline: bla
• Group members: xxx, yyy, zzz

Identification fo features of primates specific promoters (?; together with LL)

• Outline: bla
• Group members: xxx, yyy, zzz

Regulation specificity of cells and tissues (Vlad’ s group)

• Outline: bla
• Group members: xxx, yyy, zzz

Host pathogen infection relationship; influenza virus, Mycobacteria, Salomonella (Arnab)

• Outline: bla
• Group members: xxx, yyy, zzz

Searching for viruses, cryptic viruses (Arnab, mamoon, al, nico)

• Outline: bla
• Group members: xxx, yyy, zzz

Deorphanizing transcription factors (Vlad)

• Outline: bla
• Group members: xxx, yyy, zzz

Variation in small RNA population and variation in siRNA machinery (Max)

• Outline: bla
• Group members: xxx, yyy, zzz

Cellular restriction of terminal ligases in ubiquitin system (Max)

• Outline: bla
• Group members: xxx, yyy, zzz

Papers of individual cells time courses

• Outline: bla
• Group members: xxx, yyy, zzz

Extend rat gene models with CAGEscan

• Outline: Rat gene models sometimes lack a proper 5′ UTR. CAGEscan data has been produced using the same RNA (10009-101B8) as the reference FANTOM5 Helicos CAGE library CNhs10612. This experimental data can be used to propose an update of the rat gene models.
• Group members: Charles Plessy, Albin Sandelin, other people, please list yourself.

Cellular restriction of epigenomic regulation Erik A. + Andreas Lenn.

• Outline: bla
• Group members: xxx, yyy, zzz

Issues: negotiation with sample providers

Encouraged to write paper, but larger stronger papers is perhaps better?

• Outline: bla
• Group members: xxx, yyy, zzz

Talk with collaborator before the datasets is published

• Outline: bla
• Group members: xxx, yyy, zzz