Description of an optimized ChIP-seq analysis pipeline dedicated to genome wide identification of E4F1 binding sites in primary and transformed MEFs.

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Raw and processed data are available at the GEO DataSet repository under the subseries # GSE57228. E4F1 is a ubiquitously expressed zinc-finger protein of the GLI-Kruppel family that was first identified in the late eighties as a cellular transcription factor targeted by the adenoviral oncoprotein E1A13S (Ad type V) and required for the transcription of adenoviral genes (Raychaudhuri et al., 1987) [8]. It is a multifunctional factor that also acts as an atypical E3 ubiquitin ligase for p53 (Le Cam et al., 2006) [2]. Using KO mouse models we then demonstrated that E4F1 is essential for early embryonic development (Le Cam et al., 2004), for proliferation of mouse embryonic cell (Rodier et al., 2015), for the maintenance of epidermal stem cells (Lacroix et al., 2010) [6], and strikingly, for the survival of cancer cells (Hatchi et al., 2007) [4]; (Rodier et al., 2015) [10]. The latter survival phenotype was p53-independent and suggested that E4F1 was controlling a transcriptional program driving essential functions in cancer cells. To identify this program, we performed E4F1 ChIP-seq analyses in primary Mouse Embryonic Fibroblasts (MEF) and in p53(-/-), H-Ras(V12)-transformed MEFs. The program directly controlled by E4F1 was obtained by intersecting the lists of E4F1 genomic targets with the lists of genes differentially expressed in E4F1 KO and E4F1 WT cells (Rodier et al., 2015). We describe hereby how we improved our ChIP-seq analyses workflow by applying prefilters on raw data and by using a combination of two publicly available programs, Cisgenome and QESEQ.", "claims": [{"id": "claim-data-access", "statement": "Raw and processed data are available at the GEO DataSet repository under the subseries # GSE57228.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:26484288", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Raw and processed data are available at the GEO DataSet repository under the subseries # GSE57228."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The paper reports an improved ChIP-seq analysis workflow using prefilters and the combination of Cisgenome and QESEQ; the source data are available through GEO DataSet subseries GSE57228.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:26484288", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We describe hereby how we improved our ChIP-seq analyses workflow by applying prefilters on raw data and by using a combination of two publicly available programs, Cisgenome and QESEQ."}, {"asset": "source:pmid:26484288", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Raw and processed data are available at the GEO DataSet repository under the subseries # GSE57228."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The paper reports an improved ChIP-seq analysis workflow using prefilters and the combination of Cisgenome and QESEQ; the source data are available through GEO DataSet subseries GSE57228.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:26484288"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. 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