Ontology engineering

news and viewsSystematic tracking of cell fate changesJonghwan Kim & Stuart H OrkinHigh-throughput measurements across several regulatory levels provide a comprehensive view of ES-celldifferentiation.© 2010 Nature America, Inc. All rights reserved.Deciphering the regulation of eukaryoticgene expression is a formidable challengebecause of the multilayered nature of regulatorymechanisms. In an effort to decodethe complexity of molecular processes governingcell fate changes in mouse embryonicstem (ES) cells, Lu et al. 1 , in a recent issueof Nature, integrated multiple ‘omics’ datasets and systematically monitored temporalchanges in some of the key regulatory events(Fig. 1). In offering this broad view, their systemsapproach to understanding dynamicfate changes provides insight into how todeconstruct complex networks in other cellularcontexts, such as lineage specification,differentiation and somatic cell reprogramming.Cells modulate gene expression in responseto external and/or internal stimuli. Owingto the complexity of regulatory mechanisms,efforts to date have focused largely on oneaspect at a time. For example, investigatorshave studied epigenetic modification, transcription,post-transcriptional modification,translation or post-translational modificationoccurring within a sequence of events,rather than all processes in aggregate.The recent development of high-throughputtechnologies—including gene expressionprofiling; global mapping of protein-DNAinteractions; mapping of histone modificationby microarray or sequencing; proteinproteininteraction mapping and proteinabundance measurement by mass spectrometry;and gene knockdown by RNAinterference—offers the potential to observebiological phenomenon at a global level 2 . Aseach of these methods generates a wealth ofdata, data handling and analysis tools becomerate limiting in the interpretation. This is thechallenge addressed by Lu et al. 1 .ES cells are distinguished by their capacityfor perpetual self-renewal and pluripotency(the ability to differentiate into all tissues).Nanog is one of the key transcription factorsin ES cells and is known to be required formaintenance of pluripotency in mouse ESJonghwan Kim and Stuart H. Orkin are at theChildren’s Hospital Boston and Dana FarberCancer Institute, Boston, Massachusetts, USA.e-mail: stuart_orkin@dfci.harvard.eduES cellsDifferent regulatory levelsNanog downregulationDay 0 Day 1Day 3Temporal regulationHistone modificationRNA polymerase II occupancymRNA abundanceDifferentiated cellsDay 5Nuclear protein abundanceFigure 1 Systematic monitoring of differentiating ES cells. Upon knockdown of the keytranscription factor Nanog, changes in histone acetylation, RNA polymerase II occupancy, mRNAabundance and nuclear protein abundance were measured over five days of differentiation bysystems biology tools. Acquired data sets were integrated, analyzed and visualized by GATEsoftware.cells 3,4 . In their elegant experiments, Lu etal. 1 sought to introduce a single genetic perturbationby knocking down Nanog with aninducible small hairpin RNA and to examinethe consequences of this perturbation in aglobal fashion. Upon knockdown of Nanog,ES cells exit the stem cell state and differentiate.During the accompanying dynamicchanges, Lu et al. 1 measured the outcomes atfour different regulatory layers: (i) histoneH3 lysine 9 and 14 acetylation by ChIP-chip,indicating an active epigenetic signature,(ii) RNA polymerase II occupancy by ChIPchip,indicating active gene transcription,(iii) mRNA transcript abundance by expressionmicroarray, indicating an outcome oftranscription, and (iv) nuclear protein abundanceby mass spectrometry. They collecteddata for each regulatory layer at four timepoints (days 0, 1, 3 and 5 after Nanog knockdown)to monitor the temporal sequence ofevents.By comparing changes in each regulatorylayer, Lu et al. 1 observed that, in general,changes between different gene expressionsteps are moderately well correlated.However, they also found discordant regu-DataacquisitionandintegrationInteractive analysis andvisualization of datausing GATE softwareHeat map movieand/orDynamic scatter plotlation for a large number of genes. Notably,~42–53% of all proteins whose levels changesubstantially did not correlate with changesin their respective mRNA abundances. Thisdiscrepancy has been observed in lowerorganisms, such as yeast, but has been ratherunclear in the mammalian context owingto either technical limitations or improperexperimental settings 5 . Although Lu et al. 1did not address this issue further, theirresults clearly imply that additional layersof regulation beyond transcriptional control,such as translational and post-translationalmodifications, are of critical importance incell fate decisions.Using gene-ontology analysis, Lu et al. 1also observed that chromatin-modifyingenzymes are regulated by RNA polymerase IIoccupancy but not by the other three regulatorylayers. This suggests that although chromatinremodeling is known to be importantin ES cell fate decision, primary control isexerted through transcriptional regulationvia transcription-factor occupancy.A challenge in handling such large, diversedata sets is the difficulty of visualizing thedata without adequate graphical software.146 volume 28 number 2 february 2010 nature biotechnology